{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/logreplication_study1.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}22 Oct 2021, 16:59:30

{com}. do "/Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/replication_study1.do"
{txt}
{com}.                                                         *=================================================*
.                                                         * Economic Interventions, Evaluations and Trust   *
.                                                         * Devine/Turnbull-Dugarte                                                 *
.                                                         *=================================================*
. 
.                                                         
. cd "/Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication"                                                        
{res}/Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication
{txt}
{com}. use "/Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/eb75.3_2011.dta", clear
{txt}
{com}. 
.                                                                                                         ***************
.                                                                                                         **  Cleaning **
.                                                                                                         ***************
.                                                                                                         
. 
. drop if v6 == 33 | v6 == 31 | v6 == 35 | v6 == 43 | v6 == 34 // drop non-EU countries.
{txt}(4,056 observations deleted)

{com}. replace v6 = 4 if v6 == 14 // merge East/West DE
{txt}(523 real changes made)

{com}. replace v6 = 9 if v6 == 10 // merge GB/NI
{txt}(300 real changes made)

{com}. 
. keep if v6 == 13 // keep if Portugal
{txt}(26,665 observations deleted)

{com}. 
. gen treated = 1 if v651 > 11 // keep if interviewed after intervention date (i.e treated)
{txt}(803 missing values generated)

{com}. replace treated = 0 if v651 < 12
{txt}(803 real changes made)

{com}. tab treated

    {txt}treated {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        803       76.62       76.62
{txt}          1 {c |}{res}        245       23.38      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,048      100.00
{txt}
{com}. 
. recode v310 (2=0) (1=1), generate (trust_govt) // trust govt
{txt}(798 differences between v310 and trust_govt)

{com}. recode v311 (2=0) (1=1), generate (trust_plt) // trust parliament
{txt}(728 differences between v311 and trust_plt)

{com}. recode v312 (2=0) (1=1), generate (trust_eu) // trust eu
{txt}(489 differences between v312 and trust_eu)

{com}. 
. tab trust_plt treated, col nofreq

 {txt}RECODE of {c |}
      v311 {c |}
   (QA13_2 {c |}
  TRUST IN {c |}
INSTITUTIO {c |}
   NS: NAT {c |}
PARLIAMENT {c |}        treated
         ) {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}     71.96      76.67 {txt}{c |}{res}     73.09 
{txt}         1 {c |}{res}     28.04      23.33 {txt}{c |}{res}     26.91 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. 
. gen placebo = 1 if v651 >= 7 // median of the control group, including treated
{txt}(299 missing values generated)

{com}. replace placebo = 0 if v651 <7
{txt}(299 real changes made)

{com}. 
. gen placebo2 = 1 if v651 >= 7 & treated !=1 // median of control group, excluding treated
{txt}(544 missing values generated)

{com}. replace placebo2 = 0 if v651 < 7 & treated !=1
{txt}(299 real changes made)

{com}. 
. gen placebo3 = 1 if v651 >= 6 & treated !=1 // 6th day, excluding treated
{txt}(462 missing values generated)

{com}. replace placebo3 = 0 if v651 < 6 & treated !=1
{txt}(217 real changes made)

{com}. 
. gen placebo4 = 1 if v651 >= 5 & treated !=1 // 5th day, excluding treated
{txt}(358 missing values generated)

{com}. replace placebo4 = 0 if v651 < 5 & treated !=1
{txt}(113 real changes made)

{com}. 
. rename v651 day // day of interview
{res}{txt}
{com}. 
. rename v709 region // region of portugal
{res}{txt}
{com}. 
. /* Variables are recoded so that positive coefficients would equal positive effect on evaluations */
. 
. recode v140 (1=4) (2=3) (3=2) (4=1), gen(econ_index) /* variable summarises answers to v127/140. As from the documentation:
>                                                 Respondents coded 1 or 2 in V114 or V120 and coded 1 in V127 or V134 are coded 1 ("Satisfied and confident") in the index variable. 
>                                                 Respondents coded 3 or 4 in V114 or V120 and coded 1 in V127 or V134 are coded 2 ("Unsatisfied and confident") in the index variable. 
>                                                 Respondents coded 1 or 2 in V114 or V120 and coded 2 in V127 or V134 are coded 3 ("Satisfied and worried") in the index variable. 
>                                                 Respondents coded 3 or 4 in V114 or V120 and coded 2 in V127 or V134 are coded 4 ("Unsatisfied and worried") in the index variable. 
>                                                 Respondents coded 5 in V114 or V120 or coded 3 or 4 in V127 or V134 are coded 5 ("INAP") in the index variable. */
{txt}(738 differences between v140 and econ_index)

{com}. 
. recode v127 (1=3) (2=1) (3=2), gen(econ_expec) /* What are your expectations for the next twelve months: will the next twelve months be better, worse or the same, when it comes to...?
>                                                                                                 The economic situation in [Our Country]. 1 = better, 2 = worse, 3 = same, 4 = DK */
{txt}(984 differences between v127 and econ_expec)

{com}. 
. recode v114 (1=4) (2=3) (3=2) (4=1), gen(econ_evals) /* How would you judge the current situation in each of the following?
>                                                 The situation of the [nationality] economy? 1= VG 2= Rather G 3= RB 4= VB 5 = DK */
{txt}(1041 differences between v114 and econ_evals)

{com}. 
. rename v616 age
{res}{txt}
{com}. rename v614 education
{res}{txt}
{com}. rename v752 occupation
{res}{txt}
{com}. rename v615 gender
{res}{txt}
{com}. 
. label variable treated "Treatment"
{txt}
{com}. label define treated 0 "Control" 1 "Treated"
{txt}
{com}. label values treated treated
{txt}
{com}. 
. label variable age "Age (years)"
{txt}
{com}. label variable education "Education"
{txt}
{com}. label variable occupation "Occupation"
{txt}
{com}. 
. gen running = day - 11
{txt}
{com}. 
. 
.                                                                                                         *****************
.                                                                                                         ***  FIGURE 1 ***
.                                                                                                         *****************
.                                                                                                         
.                                                                                                         
.                                                                                                                                                                                 
. reg trust_plt i.treated i.education age i.occupation gender, r 
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       980
                                                {txt}F(19, 960)        =  {res}     1.02
                                                {txt}Prob > F          = {res}    0.4372
                                                {txt}R-squared         = {res}    0.0193
                                                {txt}Root MSE          =    {res} .44495

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2} -.067556{col 33}{space 2} .0341127{col 44}{space 1}   -1.98{col 53}{space 3}0.048{col 61}{space 4}-.1345001{col 74}{space 3}-.0006118
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0105614{col 33}{space 2}  .072545{col 44}{space 1}   -0.15{col 53}{space 3}0.884{col 61}{space 4}-.1529263{col 74}{space 3} .1318036
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0767821{col 33}{space 2} .0646779{col 44}{space 1}    1.19{col 53}{space 3}0.235{col 61}{space 4}-.0501442{col 74}{space 3} .2037085
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0055829{col 33}{space 2} .0648609{col 44}{space 1}    0.09{col 53}{space 3}0.931{col 61}{space 4}-.1217026{col 74}{space 3} .1328684
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .0247865{col 33}{space 2} .0581496{col 44}{space 1}    0.43{col 53}{space 3}0.670{col 61}{space 4}-.0893286{col 74}{space 3} .1389015
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0093286{col 33}{space 2} .0780327{col 44}{space 1}   -0.12{col 53}{space 3}0.905{col 61}{space 4}-.1624628{col 74}{space 3} .1438057
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2}  .075314{col 33}{space 2} .0934745{col 44}{space 1}    0.81{col 53}{space 3}0.421{col 61}{space 4} -.108124{col 74}{space 3}  .258752
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .0343944{col 33}{space 2} .1264449{col 44}{space 1}    0.27{col 53}{space 3}0.786{col 61}{space 4} -.213746{col 74}{space 3} .2825347
{txt}22 years and older  {c |}{col 21}{res}{space 2}  .049318{col 33}{space 2} .0712584{col 44}{space 1}    0.69{col 53}{space 3}0.489{col 61}{space 4}-.0905222{col 74}{space 3} .1891581
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0140076{col 33}{space 2} .0971779{col 44}{space 1}    0.14{col 53}{space 3}0.885{col 61}{space 4} -.176698{col 74}{space 3} .2047131
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.0366155{col 33}{space 2} .0728342{col 44}{space 1}   -0.50{col 53}{space 3}0.615{col 61}{space 4} -.179548{col 74}{space 3} .1063171
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0010164{col 33}{space 2}  .001464{col 44}{space 1}   -0.69{col 53}{space 3}0.488{col 61}{space 4}-.0038894{col 74}{space 3} .0018567
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0067898{col 33}{space 2} .0897555{col 44}{space 1}   -0.08{col 53}{space 3}0.940{col 61}{space 4}-.1829294{col 74}{space 3} .1693498
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0435218{col 33}{space 2} .0742791{col 44}{space 1}   -0.59{col 53}{space 3}0.558{col 61}{space 4}-.1892901{col 74}{space 3} .1022464
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0181513{col 33}{space 2} .0659135{col 44}{space 1}   -0.28{col 53}{space 3}0.783{col 61}{space 4}-.1475026{col 74}{space 3}    .1112
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0573148{col 33}{space 2} .0901178{col 44}{space 1}    0.64{col 53}{space 3}0.525{col 61}{space 4}-.1195358{col 74}{space 3} .2341653
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0277995{col 33}{space 2} .0694707{col 44}{space 1}   -0.40{col 53}{space 3}0.689{col 61}{space 4}-.1641314{col 74}{space 3} .1085324
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .0266802{col 33}{space 2} .0720143{col 44}{space 1}    0.37{col 53}{space 3}0.711{col 61}{space 4}-.1146435{col 74}{space 3} .1680038
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.0925345{col 33}{space 2} .0295599{col 44}{space 1}   -3.13{col 53}{space 3}0.002{col 61}{space 4}-.1505439{col 74}{space 3}-.0345252
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .4675517{col 33}{space 2} .1108596{col 44}{space 1}    4.22{col 53}{space 3}0.000{col 61}{space 4} .2499965{col 74}{space 3} .6851069
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store m1
{txt}
{com}. reg econ_evals i.treated i.education age i.occupation gender, r
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}     1,022
                                                {txt}F(19, 1002)       =  {res}     1.25
                                                {txt}Prob > F          = {res}    0.2083
                                                {txt}R-squared         = {res}    0.0228
                                                {txt}Root MSE          =    {res} .58005

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}         econ_evals{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2}-.1064546{col 33}{space 2} .0435433{col 44}{space 1}   -2.44{col 53}{space 3}0.015{col 61}{space 4} -.191901{col 74}{space 3}-.0210081
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2} .0893909{col 33}{space 2} .0818395{col 44}{space 1}    1.09{col 53}{space 3}0.275{col 61}{space 4}-.0712056{col 74}{space 3} .2499873
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2}  .002016{col 33}{space 2} .0809208{col 44}{space 1}    0.02{col 53}{space 3}0.980{col 61}{space 4}-.1567777{col 74}{space 3} .1608096
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .1599669{col 33}{space 2} .0900925{col 44}{space 1}    1.78{col 53}{space 3}0.076{col 61}{space 4}-.0168246{col 74}{space 3} .3367585
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .1075112{col 33}{space 2} .0905977{col 44}{space 1}    1.19{col 53}{space 3}0.236{col 61}{space 4}-.0702718{col 74}{space 3} .2852941
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0214871{col 33}{space 2} .1003221{col 44}{space 1}   -0.21{col 53}{space 3}0.830{col 61}{space 4}-.2183527{col 74}{space 3} .1753784
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .0626885{col 33}{space 2} .1137396{col 44}{space 1}    0.55{col 53}{space 3}0.582{col 61}{space 4}-.1605067{col 74}{space 3} .2858836
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} -.052491{col 33}{space 2} .1254417{col 44}{space 1}   -0.42{col 53}{space 3}0.676{col 61}{space 4}-.2986496{col 74}{space 3} .1936676
{txt}22 years and older  {c |}{col 21}{res}{space 2}-.1204175{col 33}{space 2} .1033294{col 44}{space 1}   -1.17{col 53}{space 3}0.244{col 61}{space 4}-.3231843{col 74}{space 3} .0823493
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0320724{col 33}{space 2} .1247278{col 44}{space 1}    0.26{col 53}{space 3}0.797{col 61}{space 4}-.2126853{col 74}{space 3} .2768301
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.1071435{col 33}{space 2}  .092911{col 44}{space 1}   -1.15{col 53}{space 3}0.249{col 61}{space 4}-.2894659{col 74}{space 3}  .075179
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2} .0004921{col 33}{space 2} .0017663{col 44}{space 1}    0.28{col 53}{space 3}0.781{col 61}{space 4} -.002974{col 74}{space 3} .0039583
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2} .0849027{col 33}{space 2}  .132865{col 44}{space 1}    0.64{col 53}{space 3}0.523{col 61}{space 4}-.1758227{col 74}{space 3} .3456282
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0156898{col 33}{space 2} .1071373{col 44}{space 1}   -0.15{col 53}{space 3}0.884{col 61}{space 4} -.225929{col 74}{space 3} .1945494
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0728018{col 33}{space 2} .0882583{col 44}{space 1}   -0.82{col 53}{space 3}0.410{col 61}{space 4}-.2459941{col 74}{space 3} .1003906
{txt}House persons (..)  {c |}{col 21}{res}{space 2}-.1314546{col 33}{space 2} .1101753{col 44}{space 1}   -1.19{col 53}{space 3}0.233{col 61}{space 4}-.3476554{col 74}{space 3} .0847462
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.1131238{col 33}{space 2} .0912991{col 44}{space 1}   -1.24{col 53}{space 3}0.216{col 61}{space 4}-.2922832{col 74}{space 3} .0660355
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2}-.0405552{col 33}{space 2} .0916838{col 44}{space 1}   -0.44{col 53}{space 3}0.658{col 61}{space 4}-.2204695{col 74}{space 3}  .139359
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.0448335{col 33}{space 2} .0371716{col 44}{space 1}   -1.21{col 53}{space 3}0.228{col 61}{space 4}-.1177766{col 74}{space 3} .0281095
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 1.631482{col 33}{space 2}  .140833{col 44}{space 1}   11.58{col 53}{space 3}0.000{col 61}{space 4} 1.355121{col 74}{space 3} 1.907844
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store econ1
{txt}
{com}. reg econ_expec i.treated i.education age i.occupation gender, r
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       967
                                                {txt}F(19, 947)        =  {res}     2.32
                                                {txt}Prob > F          = {res}    0.0011
                                                {txt}R-squared         = {res}    0.0382
                                                {txt}Root MSE          =    {res} .62864

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}         econ_expec{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2}  -.17052{col 33}{space 2} .0476827{col 44}{space 1}   -3.58{col 53}{space 3}0.000{col 61}{space 4} -.264096{col 74}{space 3}-.0769439
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0118512{col 33}{space 2} .1101977{col 44}{space 1}   -0.11{col 53}{space 3}0.914{col 61}{space 4}-.2281111{col 74}{space 3} .2044088
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0329362{col 33}{space 2} .1028104{col 44}{space 1}    0.32{col 53}{space 3}0.749{col 61}{space 4}-.1688263{col 74}{space 3} .2346987
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0106981{col 33}{space 2} .0985769{col 44}{space 1}    0.11{col 53}{space 3}0.914{col 61}{space 4}-.1827563{col 74}{space 3} .2041524
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2}-.0040693{col 33}{space 2} .0860692{col 44}{space 1}   -0.05{col 53}{space 3}0.962{col 61}{space 4}-.1729776{col 74}{space 3} .1648391
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.1351445{col 33}{space 2} .1103899{col 44}{space 1}   -1.22{col 53}{space 3}0.221{col 61}{space 4}-.3517816{col 74}{space 3} .0814926
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .0566709{col 33}{space 2} .1446986{col 44}{space 1}    0.39{col 53}{space 3}0.695{col 61}{space 4}-.2272961{col 74}{space 3} .3406378
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .2204867{col 33}{space 2} .1706926{col 44}{space 1}    1.29{col 53}{space 3}0.197{col 61}{space 4}-.1144927{col 74}{space 3} .5554661
{txt}22 years and older  {c |}{col 21}{res}{space 2}-.1983336{col 33}{space 2} .0883321{col 44}{space 1}   -2.25{col 53}{space 3}0.025{col 61}{space 4} -.371683{col 74}{space 3}-.0249843
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2}-.0094933{col 33}{space 2} .1475393{col 44}{space 1}   -0.06{col 53}{space 3}0.949{col 61}{space 4}-.2990352{col 74}{space 3} .2800485
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.1774807{col 33}{space 2} .0813278{col 44}{space 1}   -2.18{col 53}{space 3}0.029{col 61}{space 4}-.3370843{col 74}{space 3}-.0178772
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0041471{col 33}{space 2} .0022531{col 44}{space 1}   -1.84{col 53}{space 3}0.066{col 61}{space 4}-.0085688{col 74}{space 3} .0002746
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2} .1196467{col 33}{space 2} .1258054{col 44}{space 1}    0.95{col 53}{space 3}0.342{col 61}{space 4}-.1272428{col 74}{space 3} .3665362
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0856407{col 33}{space 2} .1037474{col 44}{space 1}   -0.83{col 53}{space 3}0.409{col 61}{space 4}-.2892421{col 74}{space 3} .1179606
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0254881{col 33}{space 2} .0881653{col 44}{space 1}   -0.29{col 53}{space 3}0.773{col 61}{space 4}-.1985101{col 74}{space 3} .1475339
{txt}House persons (..)  {c |}{col 21}{res}{space 2}  .041484{col 33}{space 2} .1231591{col 44}{space 1}    0.34{col 53}{space 3}0.736{col 61}{space 4}-.2002124{col 74}{space 3} .2831804
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0945762{col 33}{space 2}  .092892{col 44}{space 1}   -1.02{col 53}{space 3}0.309{col 61}{space 4}-.2768742{col 74}{space 3} .0877218
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2}-.0509152{col 33}{space 2} .0932622{col 44}{space 1}   -0.55{col 53}{space 3}0.585{col 61}{space 4}-.2339397{col 74}{space 3} .1321093
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.0028392{col 33}{space 2}  .042262{col 44}{space 1}   -0.07{col 53}{space 3}0.946{col 61}{space 4}-.0857772{col 74}{space 3} .0800988
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 1.698204{col 33}{space 2} .1659541{col 44}{space 1}   10.23{col 53}{space 3}0.000{col 61}{space 4} 1.372524{col 74}{space 3} 2.023884
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store econ3
{txt}
{com}. coefplot (m1, msymbol(circle) mlabel("Trust in Parliament (0/1)") mlabposition(12)) (econ1, msymbol(diamond) mlabel("Economic evaluations (1-4)") mlabposition(12)) ///
> (econ3, msymbol(triangle) mlabel("Economic expectations (1-3)") mlabposition(12)), ///
>                 keep(*.treated) xline(0, lcolor(black)) ylabel("") xtitle("Marginal effect of intervention") ///
>                 legend(off) levels(99 95) note("Confidence intervals at 99% and 95%", size(small) position(5)) scheme(538w) legend(position(6) rows(2))
{res}{txt}
{com}. graph save Figure1.gph, replace
{txt}(note: file Figure1.gph not found)
{res}{txt}(file Figure1.gph saved)

{com}. graph export Figure1.pdf, replace               
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/Figure1.pdf written in PDF format)

{com}. **********************************APPENDIX MATERIAL**********************************
. 
.                                                                                                         ******************
.                                                                                                         ***  TABLE A1 ****
.                                                                                                         ******************
. 
. sutex trust_plt treated education age occupation gender econ_eval econ_expec econ_index region, minmax file(TableA1.tex)
file {view "TableA1.tex"} saved
{txt}
{com}. 
.                                                                                                         ******************
.                                                                                                         **  TABLE A2-3  **                                                                                                      
.                                                                                                         ******************
.                                                                                                         
. by treated, sort : sutex trust_plt treated education age occupation gender econ_eval econ_expec econ_index region, minmax file(TableA2-A3.tex)
file {view "TableA2-A3.tex"} saved
file {view "TableA2-A3.tex"} saved
{txt}
{com}.         
.                                                                                                         
.                                                                                                         ******************
.                                                                                                         ***  TABLE A4 ****                                                                                                      
.                                                                                                         ******************
. latab  treated

{txt}\begin{table}[htbp]\centering
\caption{\label{freq_treated} 
\textbf{Treatment}}
\begin{tabular} {@{} l r r @{}} \\ \hline
Item& Number & Per cent \\
\hline
{res}Control&      803&       77\\
Treated&      245&       23\\
Total&    1,048&      100\\
{txt}\hline
\multicolumn{3}{@{}l}{\footnotesize{\emph{Source:} /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/eb75.3_2011.dta}}
\end{tabular}
\end{table}


{com}This table can be cross-referenced in the body of your text
with the name: freq_treated

{txt}
{com}. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A1 ***
.                                                                                                         ******************
. 
. hist day, frequency xline(11, lcolor(red)) xtitle("Day of interview") ytitle("Number of respondents") w(1) fcolor(gs10*0.5) 
{txt}(bin={res}15{txt}, start={res}2{txt}, width={res}1{txt})
{res}{txt}
{com}. graph save FigureA1.gph, replace
{txt}(note: file FigureA1.gph not found)
{res}{txt}(file FigureA1.gph saved)

{com}. graph export FigureA1.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA1.pdf written in PDF format)

{com}.                                                                                                         ******************
.                                                                                                         ***  FIGURE A2 ***
.                                                                                                         ******************
. 
. preserve
{txt}
{com}. collapse (mean) trust_plt econ_evals econ_expec, by(day)
{txt}
{com}. 
. twoway line trust_plt day, xline(11, lcolor(red)) xtitle("Day of interview") ytitle("% trust parliament") legend(off) || lfit trust_plt day if day <=11 || lfit trust_plt day if day >=11, saving(trustday, replace)
{res}{txt}(note: file trustday.gph not found)
{res}{txt}(file trustday.gph saved)

{com}. 
. twoway line econ_evals day, xline(11, lcolor(red)) xtitle("Day of interview") ytitle("Econ evaluations") legend(off) || lfit econ_evals day if day <=11 || lfit econ_evals day if day >=11, saving(evalsday, replace)
{res}{txt}(note: file evalsday.gph not found)
{res}{txt}(file evalsday.gph saved)

{com}. 
. twoway line econ_expec day, xline(11, lcolor(red)) xtitle("Day of interview") ytitle("Econ expectations") legend(off) || lfit econ_expec day if day <=11 || lfit econ_expec day if day >=11, saving(expecday, replace)
{res}{txt}(note: file expecday.gph not found)
{res}{txt}(file expecday.gph saved)

{com}. 
. gr combine trustday.gph evalsday.gph expecday.gph
{res}{txt}
{com}. graph save FigureA2.gph, replace
{txt}(note: file FigureA2.gph not found)
{res}{txt}(file FigureA2.gph saved)

{com}. graph export FigureA2.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA2.pdf written in PDF format)

{com}. restore
{txt}
{com}. 
. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A3 ***
.                                                                                                         ******************
.                                                                                                         
.                                                                                                         
. twoway (lpolyci trust_plt day if day <=12) (lpolyci trust_plt day if day >=12, legend(off) xline(12,lpattern(dash)))  (hist day, blcolor(gs10%30) fcolor(gs10%30) discrete percent legend(off) yaxis(2) yscale(alt lcolor() axis(2)) ylabel(0 " " 20 " " 40 " " 60 " " 80 " " 100 " ", labcolor() axis(2) tlcolor(black) tlwidth(thin) labsize(small) tl(0)))
{res}{txt}
{com}. gr save poly1.gph
{res}{txt}(file poly1.gph saved)

{com}. twoway (lpolyci econ_evals day if day <=12) (lpolyci econ_evals day if day >=12, legend(off) xline(12,lpattern(dash)))  (hist day, blcolor(gs10%30) fcolor(gs10%30) discrete percent legend(off) yaxis(2) yscale(alt lcolor() axis(2)) ylabel(0 " " 20 " " 40 " " 60 " " 80 " " 100 " ", labcolor() axis(2) tlcolor(black) tlwidth(thin) labsize(small) tl(0)))
{res}{txt}
{com}. gr save poly2.gph
{res}{txt}(file poly2.gph saved)

{com}. twoway (lpolyci econ_expec day if day <=12) (lpolyci econ_expec day if day >=12, legend(off) xline(12,lpattern(dash)) ytitle(Test))  (hist day, blcolor(gs10%30) fcolor(gs10%30) discrete percent legend(off) yaxis(2) yscale(alt lcolor() axis(2)) ytitle("") ylabel(0 " " 20 " " 40 " " 60 " " 80 " " 100 " ", labcolor() axis(2) tlcolor(black) tlwidth(thin) labsize(small) tl(0)))
{res}{txt}
{com}. gr save poly3.gph
{res}{txt}(file poly3.gph saved)

{com}. gr combine poly1.gph poly2.gph poly3.gph
{res}{txt}
{com}. graph save FigureA3.gph, replace
{txt}(note: file FigureA3.gph not found)
{res}{txt}(file FigureA3.gph saved)

{com}. graph export FigureA3.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA3.pdf written in PDF format)

{com}. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A4 ***
.                                                                                                         ******************
. 
. //Balance of treatmeant assignment
. logit treated i.education age i.occupation i.gender

{txt}note: 8.occupation omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-558.90871}  
Iteration 1:{space 3}log likelihood = {res:-506.54058}  
Iteration 2:{space 3}log likelihood = {res:-502.65324}  
Iteration 3:{space 3}log likelihood = {res:-502.45151}  
Iteration 4:{space 3}log likelihood = {res:-502.44901}  
Iteration 5:{space 3}log likelihood = {res:-502.44901}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,029
{txt}{col 49}LR chi2({res}18{txt}){col 67}= {res}    112.92
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-502.44901{txt}{col 49}Pseudo R2{col 67}= {res}    0.1010

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            treated{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      z{col 53}   P>|z|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.2401406{col 33}{space 2} .3722323{col 44}{space 1}   -0.65{col 53}{space 3}0.519{col 61}{space 4}-.9697025{col 74}{space 3} .4894212
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2}-.7777789{col 33}{space 2} .3542163{col 44}{space 1}   -2.20{col 53}{space 3}0.028{col 61}{space 4} -1.47203{col 74}{space 3}-.0835277
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2}-.4552097{col 33}{space 2} .3627675{col 44}{space 1}   -1.25{col 53}{space 3}0.210{col 61}{space 4}-1.166221{col 74}{space 3} .2558015
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2}-.4727459{col 33}{space 2} .3183231{col 44}{space 1}   -1.49{col 53}{space 3}0.138{col 61}{space 4}-1.096648{col 74}{space 3}  .151156
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.7207318{col 33}{space 2}  .438241{col 44}{space 1}   -1.64{col 53}{space 3}0.100{col 61}{space 4}-1.579668{col 74}{space 3} .1382047
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2}-.7438592{col 33}{space 2} .5026342{col 44}{space 1}   -1.48{col 53}{space 3}0.139{col 61}{space 4}-1.729004{col 74}{space 3} .2412858
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2}-.4403245{col 33}{space 2} .5803118{col 44}{space 1}   -0.76{col 53}{space 3}0.448{col 61}{space 4}-1.577715{col 74}{space 3} .6970657
{txt}22 years and older  {c |}{col 21}{res}{space 2}-.5526519{col 33}{space 2} .3774691{col 44}{space 1}   -1.46{col 53}{space 3}0.143{col 61}{space 4}-1.292478{col 74}{space 3} .1871739
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0202168{col 33}{space 2} .4799557{col 44}{space 1}    0.04{col 53}{space 3}0.966{col 61}{space 4}-.9204792{col 74}{space 3} .9609128
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-1.552501{col 33}{space 2} 1.030878{col 44}{space 1}   -1.51{col 53}{space 3}0.132{col 61}{space 4}-3.572985{col 74}{space 3} .4679834
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0434684{col 33}{space 2} .0079169{col 44}{space 1}   -5.49{col 53}{space 3}0.000{col 61}{space 4}-.0589852{col 74}{space 3}-.0279516
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2} .0430444{col 33}{space 2} .4658744{col 44}{space 1}    0.09{col 53}{space 3}0.926{col 61}{space 4}-.8700528{col 74}{space 3} .9561415
{txt}Other white col..)  {c |}{col 21}{res}{space 2} .2294515{col 33}{space 2} .3975067{col 44}{space 1}    0.58{col 53}{space 3}0.564{col 61}{space 4}-.5496473{col 74}{space 3}  1.00855
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2} .0889036{col 33}{space 2} .3505145{col 44}{space 1}    0.25{col 53}{space 3}0.800{col 61}{space 4}-.5980923{col 74}{space 3} .7758995
{txt}House persons (..)  {c |}{col 21}{res}{space 2}-.0210622{col 33}{space 2} .5114732{col 44}{space 1}   -0.04{col 53}{space 3}0.967{col 61}{space 4}-1.023531{col 74}{space 3} .9814069
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2} .2238461{col 33}{space 2} .3667654{col 44}{space 1}    0.61{col 53}{space 3}0.542{col 61}{space 4} -.495001{col 74}{space 3} .9426931
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .1141084{col 33}{space 2} .3953846{col 44}{space 1}    0.29{col 53}{space 3}0.773{col 61}{space 4}-.6608312{col 74}{space 3}  .889048
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}
{space 12}Female  {c |}{col 21}{res}{space 2}-.5898733{col 33}{space 2} .1598817{col 44}{space 1}   -3.69{col 53}{space 3}0.000{col 61}{space 4}-.9032357{col 74}{space 3} -.276511
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 1.169254{col 33}{space 2} .5249101{col 44}{space 1}    2.23{col 53}{space 3}0.026{col 61}{space 4} .1404486{col 74}{space 3} 2.198059
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. coefplot, xline(0) drop(_cons) xtitle("Coefficient") ytitle("Variable")
{res}{txt}
{com}. graph save FigureA4.gph, replace
{txt}(note: file FigureA4.gph not found)
{res}{txt}(file FigureA4.gph saved)

{com}. graph export FigureA4.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA4.pdf written in PDF format)

{com}. 
. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A5 ***
.                                                                                                         ******************
. 
. 
. reg trust_plt i.treated i.education age i.occupation if gender == 1, r 
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       463
                                                {txt}F(18, 444)        =  {res}     1.23
                                                {txt}Prob > F          = {res}    0.2336
                                                {txt}R-squared         = {res}    0.0503
                                                {txt}Root MSE          =    {res} .46324

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2}-.1050306{col 33}{space 2} .0475212{col 44}{space 1}   -2.21{col 53}{space 3}0.028{col 61}{space 4} -.198425{col 74}{space 3}-.0116363
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0501182{col 33}{space 2} .1148901{col 44}{space 1}   -0.44{col 53}{space 3}0.663{col 61}{space 4} -.275914{col 74}{space 3} .1756777
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .1008741{col 33}{space 2} .0933536{col 44}{space 1}    1.08{col 53}{space 3}0.280{col 61}{space 4}-.0825958{col 74}{space 3}  .284344
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0635472{col 33}{space 2} .1017631{col 44}{space 1}    0.62{col 53}{space 3}0.533{col 61}{space 4}-.1364501{col 74}{space 3} .2635444
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .0856085{col 33}{space 2} .0823377{col 44}{space 1}    1.04{col 53}{space 3}0.299{col 61}{space 4}-.0762114{col 74}{space 3} .2474285
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2} .1576508{col 33}{space 2} .1256196{col 44}{space 1}    1.25{col 53}{space 3}0.210{col 61}{space 4}-.0892321{col 74}{space 3} .4045337
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .1220919{col 33}{space 2} .1714627{col 44}{space 1}    0.71{col 53}{space 3}0.477{col 61}{space 4}-.2148874{col 74}{space 3} .4590711
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} -.039238{col 33}{space 2} .1568875{col 44}{space 1}   -0.25{col 53}{space 3}0.803{col 61}{space 4}-.3475723{col 74}{space 3} .2690963
{txt}22 years and older  {c |}{col 21}{res}{space 2} .2498827{col 33}{space 2} .1126866{col 44}{space 1}    2.22{col 53}{space 3}0.027{col 61}{space 4} .0284173{col 74}{space 3} .4713481
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0024627{col 33}{space 2} .1363485{col 44}{space 1}    0.02{col 53}{space 3}0.986{col 61}{space 4}-.2655059{col 74}{space 3} .2704314
{txt}No full-time edu..  {c |}{col 21}{res}{space 2} .3136174{col 33}{space 2} .1552283{col 44}{space 1}    2.02{col 53}{space 3}0.044{col 61}{space 4}  .008544{col 74}{space 3} .6186908
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0023454{col 33}{space 2} .0020791{col 44}{space 1}   -1.13{col 53}{space 3}0.260{col 61}{space 4}-.0064315{col 74}{space 3} .0017406
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2} .0399569{col 33}{space 2} .1247332{col 44}{space 1}    0.32{col 53}{space 3}0.749{col 61}{space 4} -.205184{col 74}{space 3} .2850977
{txt}Other white col..)  {c |}{col 21}{res}{space 2} .0215283{col 33}{space 2}  .108108{col 44}{space 1}    0.20{col 53}{space 3}0.842{col 61}{space 4}-.1909388{col 74}{space 3} .2339953
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2} .0362201{col 33}{space 2} .0961339{col 44}{space 1}    0.38{col 53}{space 3}0.707{col 61}{space 4}-.1527139{col 74}{space 3} .2251541
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .1047432{col 33}{space 2} .1601831{col 44}{space 1}    0.65{col 53}{space 3}0.514{col 61}{space 4}-.2100681{col 74}{space 3} .4195545
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2} .0729276{col 33}{space 2} .0992022{col 44}{space 1}    0.74{col 53}{space 3}0.463{col 61}{space 4}-.1220366{col 74}{space 3} .2678918
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .1508148{col 33}{space 2} .1014185{col 44}{space 1}    1.49{col 53}{space 3}0.138{col 61}{space 4}-.0485052{col 74}{space 3} .3501348
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .3358814{col 33}{space 2} .1458313{col 44}{space 1}    2.30{col 53}{space 3}0.022{col 61}{space 4} .0492761{col 74}{space 3} .6224867
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store plt_men
{txt}
{com}. 
. reg trust_plt i.treated i.education age i.occupation if  gender == 2, r 
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       517
                                                {txt}F(18, 498)        =  {res}     1.49
                                                {txt}Prob > F          = {res}    0.0884
                                                {txt}R-squared         = {res}    0.0366
                                                {txt}Root MSE          =    {res} .42098

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2}-.0148504{col 33}{space 2} .0510686{col 44}{space 1}   -0.29{col 53}{space 3}0.771{col 61}{space 4}-.1151868{col 74}{space 3}  .085486
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}  .029046{col 33}{space 2} .0939812{col 44}{space 1}    0.31{col 53}{space 3}0.757{col 61}{space 4}-.1556025{col 74}{space 3} .2136945
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0813681{col 33}{space 2} .0902496{col 44}{space 1}    0.90{col 53}{space 3}0.368{col 61}{space 4}-.0959488{col 74}{space 3}  .258685
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2}-.0342326{col 33}{space 2} .0854301{col 44}{space 1}   -0.40{col 53}{space 3}0.689{col 61}{space 4}-.2020805{col 74}{space 3} .1336153
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2}-.0368073{col 33}{space 2} .0747583{col 44}{space 1}   -0.49{col 53}{space 3}0.623{col 61}{space 4}-.1836879{col 74}{space 3} .1100733
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.1757149{col 33}{space 2} .0769593{col 44}{space 1}   -2.28{col 53}{space 3}0.023{col 61}{space 4}-.3269199{col 74}{space 3}-.0245098
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .0534352{col 33}{space 2} .1104063{col 44}{space 1}    0.48{col 53}{space 3}0.629{col 61}{space 4}-.1634843{col 74}{space 3} .2703548
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .1689774{col 33}{space 2} .1911864{col 44}{space 1}    0.88{col 53}{space 3}0.377{col 61}{space 4} -.206654{col 74}{space 3} .5446088
{txt}22 years and older  {c |}{col 21}{res}{space 2}-.1079934{col 33}{space 2} .0698824{col 44}{space 1}   -1.55{col 53}{space 3}0.123{col 61}{space 4} -.245294{col 74}{space 3} .0293072
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0618483{col 33}{space 2} .1382122{col 44}{space 1}    0.45{col 53}{space 3}0.655{col 61}{space 4}-.2097025{col 74}{space 3} .3333992
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.1988168{col 33}{space 2}  .067929{col 44}{space 1}   -2.93{col 53}{space 3}0.004{col 61}{space 4}-.3322796{col 74}{space 3} -.065354
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2} .0013611{col 33}{space 2} .0020458{col 44}{space 1}    0.67{col 53}{space 3}0.506{col 61}{space 4}-.0026584{col 74}{space 3} .0053805
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0610952{col 33}{space 2} .1240379{col 44}{space 1}   -0.49{col 53}{space 3}0.623{col 61}{space 4}-.3047974{col 74}{space 3} .1826069
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.1139584{col 33}{space 2} .1012555{col 44}{space 1}   -1.13{col 53}{space 3}0.261{col 61}{space 4}-.3128991{col 74}{space 3} .0849823
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2} -.103398{col 33}{space 2} .0917168{col 44}{space 1}   -1.13{col 53}{space 3}0.260{col 61}{space 4}-.2835976{col 74}{space 3} .0768017
{txt}House persons (..)  {c |}{col 21}{res}{space 2}-.0418214{col 33}{space 2} .1145243{col 44}{space 1}   -0.37{col 53}{space 3}0.715{col 61}{space 4}-.2668318{col 74}{space 3} .1831889
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2} -.138488{col 33}{space 2} .0961722{col 44}{space 1}   -1.44{col 53}{space 3}0.150{col 61}{space 4}-.3274413{col 74}{space 3} .0504653
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2}-.1076709{col 33}{space 2} .1035298{col 44}{space 1}   -1.04{col 53}{space 3}0.299{col 61}{space 4}  -.31108{col 74}{space 3} .0957382
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .2731819{col 33}{space 2} .1348038{col 44}{space 1}    2.03{col 53}{space 3}0.043{col 61}{space 4} .0083276{col 74}{space 3} .5380362
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store plt_women
{txt}
{com}. 
. reg econ_evals i.treated education age occupation if gender == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       468
{txt}{hline 13}{c +}{hline 34}   F(4, 463)       = {res}     0.89
{txt}       Model {c |} {res} 1.27603815         4  .319009537   {txt}Prob > F        ={res}    0.4717
{txt}    Residual {c |} {res}  166.59362       463  .359813434   {txt}R-squared       ={res}    0.0076
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0010
{txt}       Total {c |} {res} 167.869658       467  .359463936   {txt}Root MSE        =   {res} .59984

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1057984{col 26}{space 2} .0626419{col 37}{space 1}   -1.69{col 46}{space 3}0.092{col 54}{space 4} -.228896{col 67}{space 3} .0172992
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0067681{col 26}{space 2}  .009822{col 37}{space 1}    0.69{col 46}{space 3}0.491{col 54}{space 4}-.0125331{col 67}{space 3} .0260693
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0003608{col 26}{space 2} .0017973{col 37}{space 1}    0.20{col 46}{space 3}0.841{col 54}{space 4}-.0031711{col 67}{space 3} .0038927
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0034976{col 26}{space 2} .0139673{col 37}{space 1}   -0.25{col 46}{space 3}0.802{col 54}{space 4}-.0309447{col 67}{space 3} .0239495
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.555404{col 26}{space 2} .1200034{col 37}{space 1}   12.96{col 46}{space 3}0.000{col 54}{space 4} 1.319585{col 67}{space 3} 1.791223
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       468
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.treated education age occupation}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1057984{col 26}{space 2} .0626419{col 37}{space 1}   -1.69{col 46}{space 3}0.092{col 54}{space 4} -.228896{col 67}{space 3} .0172992
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0067681{col 26}{space 2}  .009822{col 37}{space 1}    0.69{col 46}{space 3}0.491{col 54}{space 4}-.0125331{col 67}{space 3} .0260693
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0003608{col 26}{space 2} .0017973{col 37}{space 1}    0.20{col 46}{space 3}0.841{col 54}{space 4}-.0031711{col 67}{space 3} .0038927
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0034976{col 26}{space 2} .0139673{col 37}{space 1}   -0.25{col 46}{space 3}0.802{col 54}{space 4}-.0309447{col 67}{space 3} .0239495
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. est store evals_men
{txt}
{com}. 
. reg econ_evals i.treated education age occupation if gender == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       554
{txt}{hline 13}{c +}{hline 34}   F(4, 549)       = {res}     0.83
{txt}       Model {c |} {res} 1.06570812         4  .266427031   {txt}Prob > F        ={res}    0.5040
{txt}    Residual {c |} {res} 175.434292       549  .319552444   {txt}R-squared       ={res}    0.0060
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0012
{txt}       Total {c |} {res}      176.5       553  .319168174   {txt}Root MSE        =   {res} .56529

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1032623{col 26}{space 2} .0662182{col 37}{space 1}   -1.56{col 46}{space 3}0.119{col 54}{space 4}-.2333344{col 67}{space 3} .0268098
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0048618{col 26}{space 2} .0072245{col 37}{space 1}   -0.67{col 46}{space 3}0.501{col 54}{space 4}-.0190527{col 67}{space 3} .0093292
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009961{col 26}{space 2} .0015479{col 37}{space 1}   -0.64{col 46}{space 3}0.520{col 54}{space 4}-.0040367{col 67}{space 3} .0020444
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0060704{col 26}{space 2} .0133105{col 37}{space 1}   -0.46{col 46}{space 3}0.649{col 54}{space 4}-.0322161{col 67}{space 3} .0200753
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.615784{col 26}{space 2} .0960794{col 37}{space 1}   16.82{col 46}{space 3}0.000{col 54}{space 4} 1.427055{col 67}{space 3} 1.804512
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       554
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.treated education age occupation}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1032623{col 26}{space 2} .0662182{col 37}{space 1}   -1.56{col 46}{space 3}0.119{col 54}{space 4}-.2333344{col 67}{space 3} .0268098
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0048618{col 26}{space 2} .0072245{col 37}{space 1}   -0.67{col 46}{space 3}0.501{col 54}{space 4}-.0190527{col 67}{space 3} .0093292
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009961{col 26}{space 2} .0015479{col 37}{space 1}   -0.64{col 46}{space 3}0.520{col 54}{space 4}-.0040367{col 67}{space 3} .0020444
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0060704{col 26}{space 2} .0133105{col 37}{space 1}   -0.46{col 46}{space 3}0.649{col 54}{space 4}-.0322161{col 67}{space 3} .0200753
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. est store evals_women
{txt}
{com}. 
. reg econ_expec i.treated education age occupation if gender == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       447
{txt}{hline 13}{c +}{hline 34}   F(4, 442)       = {res}     2.73
{txt}       Model {c |} {res} 4.27500928         4  1.06875232   {txt}Prob > F        ={res}    0.0288
{txt}    Residual {c |} {res} 173.044901       442  .391504301   {txt}R-squared       ={res}    0.0241
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0153
{txt}       Total {c |} {res} 177.319911       446  .397578275   {txt}Root MSE        =   {res}  .6257

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1792693{col 26}{space 2} .0667343{col 37}{space 1}   -2.69{col 46}{space 3}0.007{col 54}{space 4}-.3104253{col 67}{space 3}-.0481132
{txt}{space 3}education {c |}{col 14}{res}{space 2}  .007542{col 26}{space 2} .0105225{col 37}{space 1}    0.72{col 46}{space 3}0.474{col 54}{space 4}-.0131382{col 67}{space 3} .0282223
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0022002{col 26}{space 2} .0019745{col 37}{space 1}   -1.11{col 46}{space 3}0.266{col 54}{space 4}-.0060807{col 67}{space 3} .0016803
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0105071{col 26}{space 2} .0149088{col 37}{space 1}   -0.70{col 46}{space 3}0.481{col 54}{space 4} -.039808{col 67}{space 3} .0187938
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.579991{col 26}{space 2} .1314418{col 37}{space 1}   12.02{col 46}{space 3}0.000{col 54}{space 4} 1.321662{col 67}{space 3} 1.838319
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       447
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.treated education age occupation}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1792693{col 26}{space 2} .0667343{col 37}{space 1}   -2.69{col 46}{space 3}0.007{col 54}{space 4}-.3104253{col 67}{space 3}-.0481132
{txt}{space 3}education {c |}{col 14}{res}{space 2}  .007542{col 26}{space 2} .0105225{col 37}{space 1}    0.72{col 46}{space 3}0.474{col 54}{space 4}-.0131382{col 67}{space 3} .0282223
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0022002{col 26}{space 2} .0019745{col 37}{space 1}   -1.11{col 46}{space 3}0.266{col 54}{space 4}-.0060807{col 67}{space 3} .0016803
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0105071{col 26}{space 2} .0149088{col 37}{space 1}   -0.70{col 46}{space 3}0.481{col 54}{space 4} -.039808{col 67}{space 3} .0187938
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. est store expec_men
{txt}
{com}. 
. reg econ_expec i.treated education age occupation if gender == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       520
{txt}{hline 13}{c +}{hline 34}   F(4, 515)       = {res}     4.39
{txt}       Model {c |} {res} 6.98241007         4  1.74560252   {txt}Prob > F        ={res}    0.0017
{txt}    Residual {c |} {res} 204.769513       515  .397610705   {txt}R-squared       ={res}    0.0330
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0255
{txt}       Total {c |} {res} 211.751923       519  .407999852   {txt}Root MSE        =   {res} .63056

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1569863{col 26}{space 2} .0760955{col 37}{space 1}   -2.06{col 46}{space 3}0.040{col 54}{space 4} -.306482{col 67}{space 3}-.0074906
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0174141{col 26}{space 2}  .008387{col 37}{space 1}   -2.08{col 46}{space 3}0.038{col 54}{space 4} -.033891{col 67}{space 3}-.0009372
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0069211{col 26}{space 2} .0018074{col 37}{space 1}   -3.83{col 46}{space 3}0.000{col 54}{space 4}-.0104719{col 67}{space 3}-.0033704
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0046153{col 26}{space 2}  .015386{col 37}{space 1}    0.30{col 46}{space 3}0.764{col 54}{space 4}-.0256116{col 67}{space 3} .0348423
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.810858{col 26}{space 2} .1109041{col 37}{space 1}   16.33{col 46}{space 3}0.000{col 54}{space 4} 1.592978{col 67}{space 3} 2.028738
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       520
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.treated education age occupation}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1569863{col 26}{space 2} .0760955{col 37}{space 1}   -2.06{col 46}{space 3}0.040{col 54}{space 4} -.306482{col 67}{space 3}-.0074906
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0174141{col 26}{space 2}  .008387{col 37}{space 1}   -2.08{col 46}{space 3}0.038{col 54}{space 4} -.033891{col 67}{space 3}-.0009372
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0069211{col 26}{space 2} .0018074{col 37}{space 1}   -3.83{col 46}{space 3}0.000{col 54}{space 4}-.0104719{col 67}{space 3}-.0033704
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0046153{col 26}{space 2}  .015386{col 37}{space 1}    0.30{col 46}{space 3}0.764{col 54}{space 4}-.0256116{col 67}{space 3} .0348423
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. est store expec_women
{txt}
{com}. 
. coefplot plt_men plt_women evals_men evals_women expec_men expec_women, ///
>                 keep(*.treated) xline(0) xtitle("Marginal Effect of Intervention") ///
>                 levels(99 95) ylabel("") note("Confidence intervals at 99% and 95%", size(small) position(5)) ///
>                 plotlabels("Trust Parliament (Men)" "Trust Parliament (Women)" "Evaluations (Men)" "Evaluations (Women)" ///
>                 "Expectations (Men)" "Expectations (Women)") legend(position(6) rows(2))
{res}{txt}
{com}. graph save FigureA5.gph, replace
{txt}(note: file FigureA5.gph not found)
{res}{txt}(file FigureA5.gph saved)

{com}. graph export FigureA5.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA5.pdf written in PDF format)

{com}.                 
. 
.                                                                                                         ******************
.                                                                                                         ***  TABLE A5 ***
.                                                                                                         ******************
. 
. reg trust_plt i.treated i.education age i.occupation gender, r 
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       980
                                                {txt}F(19, 960)        =  {res}     1.02
                                                {txt}Prob > F          = {res}    0.4372
                                                {txt}R-squared         = {res}    0.0193
                                                {txt}Root MSE          =    {res} .44495

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2} -.067556{col 33}{space 2} .0341127{col 44}{space 1}   -1.98{col 53}{space 3}0.048{col 61}{space 4}-.1345001{col 74}{space 3}-.0006118
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0105614{col 33}{space 2}  .072545{col 44}{space 1}   -0.15{col 53}{space 3}0.884{col 61}{space 4}-.1529263{col 74}{space 3} .1318036
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0767821{col 33}{space 2} .0646779{col 44}{space 1}    1.19{col 53}{space 3}0.235{col 61}{space 4}-.0501442{col 74}{space 3} .2037085
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0055829{col 33}{space 2} .0648609{col 44}{space 1}    0.09{col 53}{space 3}0.931{col 61}{space 4}-.1217026{col 74}{space 3} .1328684
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .0247865{col 33}{space 2} .0581496{col 44}{space 1}    0.43{col 53}{space 3}0.670{col 61}{space 4}-.0893286{col 74}{space 3} .1389015
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0093286{col 33}{space 2} .0780327{col 44}{space 1}   -0.12{col 53}{space 3}0.905{col 61}{space 4}-.1624628{col 74}{space 3} .1438057
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2}  .075314{col 33}{space 2} .0934745{col 44}{space 1}    0.81{col 53}{space 3}0.421{col 61}{space 4} -.108124{col 74}{space 3}  .258752
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .0343944{col 33}{space 2} .1264449{col 44}{space 1}    0.27{col 53}{space 3}0.786{col 61}{space 4} -.213746{col 74}{space 3} .2825347
{txt}22 years and older  {c |}{col 21}{res}{space 2}  .049318{col 33}{space 2} .0712584{col 44}{space 1}    0.69{col 53}{space 3}0.489{col 61}{space 4}-.0905222{col 74}{space 3} .1891581
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0140076{col 33}{space 2} .0971779{col 44}{space 1}    0.14{col 53}{space 3}0.885{col 61}{space 4} -.176698{col 74}{space 3} .2047131
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.0366155{col 33}{space 2} .0728342{col 44}{space 1}   -0.50{col 53}{space 3}0.615{col 61}{space 4} -.179548{col 74}{space 3} .1063171
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0010164{col 33}{space 2}  .001464{col 44}{space 1}   -0.69{col 53}{space 3}0.488{col 61}{space 4}-.0038894{col 74}{space 3} .0018567
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0067898{col 33}{space 2} .0897555{col 44}{space 1}   -0.08{col 53}{space 3}0.940{col 61}{space 4}-.1829294{col 74}{space 3} .1693498
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0435218{col 33}{space 2} .0742791{col 44}{space 1}   -0.59{col 53}{space 3}0.558{col 61}{space 4}-.1892901{col 74}{space 3} .1022464
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0181513{col 33}{space 2} .0659135{col 44}{space 1}   -0.28{col 53}{space 3}0.783{col 61}{space 4}-.1475026{col 74}{space 3}    .1112
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0573148{col 33}{space 2} .0901178{col 44}{space 1}    0.64{col 53}{space 3}0.525{col 61}{space 4}-.1195358{col 74}{space 3} .2341653
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0277995{col 33}{space 2} .0694707{col 44}{space 1}   -0.40{col 53}{space 3}0.689{col 61}{space 4}-.1641314{col 74}{space 3} .1085324
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .0266802{col 33}{space 2} .0720143{col 44}{space 1}    0.37{col 53}{space 3}0.711{col 61}{space 4}-.1146435{col 74}{space 3} .1680038
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.0925345{col 33}{space 2} .0295599{col 44}{space 1}   -3.13{col 53}{space 3}0.002{col 61}{space 4}-.1505439{col 74}{space 3}-.0345252
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .4675517{col 33}{space 2} .1108596{col 44}{space 1}    4.22{col 53}{space 3}0.000{col 61}{space 4} .2499965{col 74}{space 3} .6851069
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store m1
{txt}
{com}. * Government
. reg trust_govt i.treated i.education age i.occupation gender, r  // not significant
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       986
                                                {txt}F(19, 966)        =  {res}     1.06
                                                {txt}Prob > F          = {res}    0.3836
                                                {txt}R-squared         = {res}    0.0199
                                                {txt}Root MSE          =    {res} .40368

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}         trust_govt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2} .0041233{col 33}{space 2} .0317467{col 44}{space 1}    0.13{col 53}{space 3}0.897{col 61}{space 4}-.0581772{col 74}{space 3} .0664237
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2} .0308158{col 33}{space 2} .0695271{col 44}{space 1}    0.44{col 53}{space 3}0.658{col 61}{space 4}-.1056258{col 74}{space 3} .1672573
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0559468{col 33}{space 2} .0597682{col 44}{space 1}    0.94{col 53}{space 3}0.349{col 61}{space 4}-.0613437{col 74}{space 3} .1732373
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2}-.0267356{col 33}{space 2} .0593259{col 44}{space 1}   -0.45{col 53}{space 3}0.652{col 61}{space 4}-.1431582{col 74}{space 3} .0896869
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .0446851{col 33}{space 2} .0559529{col 44}{space 1}    0.80{col 53}{space 3}0.425{col 61}{space 4}-.0651181{col 74}{space 3} .1544883
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0746399{col 33}{space 2} .0616093{col 44}{space 1}   -1.21{col 53}{space 3}0.226{col 61}{space 4}-.1955433{col 74}{space 3} .0462635
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .1209305{col 33}{space 2} .0929577{col 44}{space 1}    1.30{col 53}{space 3}0.194{col 61}{space 4}-.0614919{col 74}{space 3} .3033529
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .1118571{col 33}{space 2} .1176923{col 44}{space 1}    0.95{col 53}{space 3}0.342{col 61}{space 4}-.1191049{col 74}{space 3} .3428191
{txt}22 years and older  {c |}{col 21}{res}{space 2} .0171334{col 33}{space 2} .0659848{col 44}{space 1}    0.26{col 53}{space 3}0.795{col 61}{space 4}-.1123566{col 74}{space 3} .1466234
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0299907{col 33}{space 2} .0841756{col 44}{space 1}    0.36{col 53}{space 3}0.722{col 61}{space 4}-.1351975{col 74}{space 3} .1951788
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.0285996{col 33}{space 2}  .068475{col 44}{space 1}   -0.42{col 53}{space 3}0.676{col 61}{space 4}-.1629765{col 74}{space 3} .1057773
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2} .0007688{col 33}{space 2} .0013197{col 44}{space 1}    0.58{col 53}{space 3}0.560{col 61}{space 4}-.0018209{col 74}{space 3} .0033585
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0257591{col 33}{space 2} .0794944{col 44}{space 1}   -0.32{col 53}{space 3}0.746{col 61}{space 4}-.1817607{col 74}{space 3} .1302425
{txt}Other white col..)  {c |}{col 21}{res}{space 2} .0229636{col 33}{space 2} .0680247{col 44}{space 1}    0.34{col 53}{space 3}0.736{col 61}{space 4}-.1105297{col 74}{space 3} .1564569
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2} .0213327{col 33}{space 2} .0588303{col 44}{space 1}    0.36{col 53}{space 3}0.717{col 61}{space 4}-.0941171{col 74}{space 3} .1367826
{txt}House persons (..)  {c |}{col 21}{res}{space 2}-.0208621{col 33}{space 2} .0751716{col 44}{space 1}   -0.28{col 53}{space 3}0.781{col 61}{space 4}-.1683805{col 74}{space 3} .1266563
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0009668{col 33}{space 2} .0618249{col 44}{space 1}   -0.02{col 53}{space 3}0.988{col 61}{space 4}-.1222934{col 74}{space 3} .1203597
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .0302032{col 33}{space 2} .0662443{col 44}{space 1}    0.46{col 53}{space 3}0.649{col 61}{space 4}-.0997961{col 74}{space 3} .1602026
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.0813923{col 33}{space 2} .0270858{col 44}{space 1}   -3.00{col 53}{space 3}0.003{col 61}{space 4} -.134546{col 74}{space 3}-.0282386
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .2677306{col 33}{space 2}  .100379{col 44}{space 1}    2.67{col 53}{space 3}0.008{col 61}{space 4} .0707445{col 74}{space 3} .4647167
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store m2
{txt}
{com}. * EU
. reg trust_eu i.treated i.education age i.occupation gender, r   // not significant
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       924
                                                {txt}F(19, 904)        =  {res}     2.95
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0495
                                                {txt}Root MSE          =    {res} .49262

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}           trust_eu{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2} -.020094{col 33}{space 2} .0391387{col 44}{space 1}   -0.51{col 53}{space 3}0.608{col 61}{space 4}-.0969073{col 74}{space 3} .0567193
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0801319{col 33}{space 2} .0898825{col 44}{space 1}   -0.89{col 53}{space 3}0.373{col 61}{space 4}-.2565346{col 74}{space 3} .0962707
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0434564{col 33}{space 2} .0735294{col 44}{space 1}    0.59{col 53}{space 3}0.555{col 61}{space 4}-.1008519{col 74}{space 3} .1877646
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0269036{col 33}{space 2} .0763079{col 44}{space 1}    0.35{col 53}{space 3}0.724{col 61}{space 4}-.1228576{col 74}{space 3} .1766648
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2}  .024807{col 33}{space 2} .0681702{col 44}{space 1}    0.36{col 53}{space 3}0.716{col 61}{space 4}-.1089832{col 74}{space 3} .1585972
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2} .0133371{col 33}{space 2} .0912456{col 44}{space 1}    0.15{col 53}{space 3}0.884{col 61}{space 4}-.1657407{col 74}{space 3} .1924148
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .0403545{col 33}{space 2}  .101286{col 44}{space 1}    0.40{col 53}{space 3}0.690{col 61}{space 4}-.1584286{col 74}{space 3} .2391376
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .0916316{col 33}{space 2} .1284872{col 44}{space 1}    0.71{col 53}{space 3}0.476{col 61}{space 4}-.1605364{col 74}{space 3} .3437995
{txt}22 years and older  {c |}{col 21}{res}{space 2}  .123011{col 33}{space 2} .0793545{col 44}{space 1}    1.55{col 53}{space 3}0.121{col 61}{space 4}-.0327294{col 74}{space 3} .2787515
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0728868{col 33}{space 2} .1059389{col 44}{space 1}    0.69{col 53}{space 3}0.492{col 61}{space 4} -.135028{col 74}{space 3} .2808015
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.1530078{col 33}{space 2} .0859843{col 44}{space 1}   -1.78{col 53}{space 3}0.075{col 61}{space 4}-.3217599{col 74}{space 3} .0157443
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0023343{col 33}{space 2} .0016695{col 44}{space 1}   -1.40{col 53}{space 3}0.162{col 61}{space 4}-.0056109{col 74}{space 3} .0009423
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2} .0516834{col 33}{space 2} .0951379{col 44}{space 1}    0.54{col 53}{space 3}0.587{col 61}{space 4}-.1350335{col 74}{space 3} .2384002
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0415124{col 33}{space 2} .0854892{col 44}{space 1}   -0.49{col 53}{space 3}0.627{col 61}{space 4}-.2092928{col 74}{space 3} .1262681
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0698925{col 33}{space 2} .0733249{col 44}{space 1}   -0.95{col 53}{space 3}0.341{col 61}{space 4}-.2137994{col 74}{space 3} .0740144
{txt}House persons (..)  {c |}{col 21}{res}{space 2}-.1185433{col 33}{space 2}  .098478{col 44}{space 1}   -1.20{col 53}{space 3}0.229{col 61}{space 4}-.3118153{col 74}{space 3} .0747287
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0619159{col 33}{space 2}  .077419{col 44}{space 1}   -0.80{col 53}{space 3}0.424{col 61}{space 4}-.2138577{col 74}{space 3} .0900259
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .0031396{col 33}{space 2} .0804222{col 44}{space 1}    0.04{col 53}{space 3}0.969{col 61}{space 4}-.1546965{col 74}{space 3} .1609756
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.1129785{col 33}{space 2} .0333913{col 44}{space 1}   -3.38{col 53}{space 3}0.001{col 61}{space 4}-.1785119{col 74}{space 3}-.0474451
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .7863957{col 33}{space 2} .1221739{col 44}{space 1}    6.44{col 53}{space 3}0.000{col 61}{space 4} .5466182{col 74}{space 3} 1.026173
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store m3
{txt}
{com}. ** Robustness: Regional effect
. reg trust_plt i.treated i.education age i.occupation gender i.region, r  // no regions significant
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       980
                                                {txt}F(23, 956)        =  {res}     0.97
                                                {txt}Prob > F          = {res}    0.4984
                                                {txt}R-squared         = {res}    0.0221
                                                {txt}Root MSE          =    {res} .44525

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2}-.0632988{col 33}{space 2} .0344731{col 44}{space 1}   -1.84{col 53}{space 3}0.067{col 61}{space 4}-.1309504{col 74}{space 3} .0043528
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2} -.016772{col 33}{space 2} .0731861{col 44}{space 1}   -0.23{col 53}{space 3}0.819{col 61}{space 4}-.1603961{col 74}{space 3}  .126852
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0695241{col 33}{space 2} .0649734{col 44}{space 1}    1.07{col 53}{space 3}0.285{col 61}{space 4}-.0579829{col 74}{space 3} .1970311
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0019794{col 33}{space 2} .0658922{col 44}{space 1}    0.03{col 53}{space 3}0.976{col 61}{space 4}-.1273306{col 74}{space 3} .1312894
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2}   .01795{col 33}{space 2} .0591118{col 44}{space 1}    0.30{col 53}{space 3}0.761{col 61}{space 4}-.0980538{col 74}{space 3} .1339538
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0128761{col 33}{space 2} .0779083{col 44}{space 1}   -0.17{col 53}{space 3}0.869{col 61}{space 4}-.1657672{col 74}{space 3}  .140015
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .0674341{col 33}{space 2} .0940143{col 44}{space 1}    0.72{col 53}{space 3}0.473{col 61}{space 4}-.1170642{col 74}{space 3} .2519323
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .0353669{col 33}{space 2} .1261768{col 44}{space 1}    0.28{col 53}{space 3}0.779{col 61}{space 4}-.2122486{col 74}{space 3} .2829825
{txt}22 years and older  {c |}{col 21}{res}{space 2} .0385472{col 33}{space 2} .0713049{col 44}{space 1}    0.54{col 53}{space 3}0.589{col 61}{space 4}-.1013851{col 74}{space 3} .1784794
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0117028{col 33}{space 2} .0981038{col 44}{space 1}    0.12{col 53}{space 3}0.905{col 61}{space 4}-.1808209{col 74}{space 3} .2042265
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.0274365{col 33}{space 2} .0738216{col 44}{space 1}   -0.37{col 53}{space 3}0.710{col 61}{space 4}-.1723076{col 74}{space 3} .1174347
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0010603{col 33}{space 2} .0014709{col 44}{space 1}   -0.72{col 53}{space 3}0.471{col 61}{space 4}-.0039469{col 74}{space 3} .0018264
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0036566{col 33}{space 2} .0894889{col 44}{space 1}   -0.04{col 53}{space 3}0.967{col 61}{space 4}-.1792739{col 74}{space 3} .1719608
{txt}Other white col..)  {c |}{col 21}{res}{space 2} -.038873{col 33}{space 2} .0745271{col 44}{space 1}   -0.52{col 53}{space 3}0.602{col 61}{space 4}-.1851286{col 74}{space 3} .1073826
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0093346{col 33}{space 2} .0665867{col 44}{space 1}   -0.14{col 53}{space 3}0.889{col 61}{space 4}-.1400075{col 74}{space 3} .1213383
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0674921{col 33}{space 2} .0908426{col 44}{space 1}    0.74{col 53}{space 3}0.458{col 61}{space 4}-.1107819{col 74}{space 3} .2457661
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0158298{col 33}{space 2}  .070109{col 44}{space 1}   -0.23{col 53}{space 3}0.821{col 61}{space 4}-.1534151{col 74}{space 3} .1217555
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .0340562{col 33}{space 2} .0725977{col 44}{space 1}    0.47{col 53}{space 3}0.639{col 61}{space 4}-.1084131{col 74}{space 3} .1765255
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2} -.091874{col 33}{space 2} .0296998{col 44}{space 1}   -3.09{col 53}{space 3}0.002{col 61}{space 4}-.1501583{col 74}{space 3}-.0335897
{txt}{space 19} {c |}
{space 13}region {c |}
{space 12}Centro  {c |}{col 21}{res}{space 2}-.0134368{col 33}{space 2}  .036155{col 44}{space 1}   -0.37{col 53}{space 3}0.710{col 61}{space 4}-.0843891{col 74}{space 3} .0575155
{txt}{space 12}Lisboa  {c |}{col 21}{res}{space 2} .0187989{col 33}{space 2} .0380487{col 44}{space 1}    0.49{col 53}{space 3}0.621{col 61}{space 4}-.0558698{col 74}{space 3} .0934675
{txt}{space 10}Alentejo  {c |}{col 21}{res}{space 2}  .070541{col 33}{space 2} .0683482{col 44}{space 1}    1.03{col 53}{space 3}0.302{col 61}{space 4}-.0635888{col 74}{space 3} .2046708
{txt}{space 11}Algarve  {c |}{col 21}{res}{space 2}-.0573263{col 33}{space 2} .0642849{col 44}{space 1}   -0.89{col 53}{space 3}0.373{col 61}{space 4}-.1834822{col 74}{space 3} .0688296
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2}  .460088{col 33}{space 2} .1118662{col 44}{space 1}    4.11{col 53}{space 3}0.000{col 61}{space 4} .2405564{col 74}{space 3} .6796196
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store m4
{txt}
{com}. 
. esttab m1 m2 m3 m4 using TableA5.tex, replace se scalars(bic) label booktabs nobaselevels star(+ 0.10 * 0.05 ** 0.01 *** 0.001) ///
> mtitles("Parliament" "Government" "European Union" "With Region FE") ///
> order (1.treated gender *.education age *.occupation) ///
> coeflabels(1.treated "Treated" gender "Gender" 2.education "15 years" 3.education "16 years" 4.education "17 years"  5.education "18 years" 6.education "19 years" 7.education "20 years" ///
> 8.education "21 years" 9.education "22+ years" 10.education "Still studying" 11.education "No full-time education" age "Age" ///
> 2.occupation "Managers" 3.occupation "Other white collar" 4.occupation "Manual workers" 5.occupation "House persons" 6.occupation "Unemployed" 7.occupation "Retired") ///
>  indicate("Region Fixed Effect = *.region", labels("\checkmark" "")) ///
> title(Results of the intervention on trust in Parliament, Government and the EU (Average Marginal Effects Reported) \label{c -(}tab:results1{c )-}) 
{res}{txt}(note: file TableA5.tex not found)
(output written to {browse  `"TableA5.tex"'})

{com}. 
.                                                                                                         ******************
.                                                                                                         ***  TABLE A6 ***
.                                                                                                         ******************
. 
. esttab  m1 econ1 econ3 using TableA6.tex, replace se star(+ 0.10 * 0.05 ** 0.01 *** 0.001) label booktabs nobaselevels ///
> mtitles ("Trust in Parliament" "Evaluations" "Expectations") ///
> order (1.treated gender *.education age *.occupation) ///
> coeflabels(1.treated "Treated" gender "Gender" 2.education "15 years" 3.education "16 years" 4.education "17 years"  5.education "18 years" 6.education "19 years" 7.education "20 years" ///
> 8.education "21 years" 9.education "22+ years" 10.education "Still studying" 11.education "No full-time education" age "Age" ///
> 2.occupation "Managers" 3.occupation "Other white collar" 4.occupation "Manual workers" 5.occupation "House persons" 6.occupation "Unemployed" 7.occupation "Retired") ///
> title(Main models as presented in figure \ref{c -(}fig:intervention_meff{c )-} (Average Marginal Effects Reported) \label{c -(}tab:main_mods{c )-})
{res}{txt}(note: file TableA6.tex not found)
(output written to {browse  `"TableA6.tex"'})

{com}. 
. 
.                                                                                                         ******************
.                                                                                                         ***  TABLE A7 ***
.                                                                                                         ******************
. 
. reg trust_plt i.placebo i.education age i.occupation gender i.region, r
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       980
                                                {txt}F(23, 956)        =  {res}     0.83
                                                {txt}Prob > F          = {res}    0.6975
                                                {txt}R-squared         = {res}    0.0190
                                                {txt}Root MSE          =    {res} .44596

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}1.placebo {c |}{col 21}{res}{space 2}-.0007303{col 33}{space 2} .0322824{col 44}{space 1}   -0.02{col 53}{space 3}0.982{col 61}{space 4}-.0640829{col 74}{space 3} .0626223
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0186326{col 33}{space 2} .0735837{col 44}{space 1}   -0.25{col 53}{space 3}0.800{col 61}{space 4}-.1630368{col 74}{space 3} .1257716
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0745555{col 33}{space 2} .0654795{col 44}{space 1}    1.14{col 53}{space 3}0.255{col 61}{space 4}-.0539447{col 74}{space 3} .2030556
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0021231{col 33}{space 2} .0664288{col 44}{space 1}    0.03{col 53}{space 3}0.975{col 61}{space 4}-.1282401{col 74}{space 3} .1324862
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .0203531{col 33}{space 2}  .059434{col 44}{space 1}    0.34{col 53}{space 3}0.732{col 61}{space 4} -.096283{col 74}{space 3} .1369892
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0091801{col 33}{space 2}  .078046{col 44}{space 1}   -0.12{col 53}{space 3}0.906{col 61}{space 4}-.1623414{col 74}{space 3} .1439811
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2}  .071678{col 33}{space 2}  .093014{col 44}{space 1}    0.77{col 53}{space 3}0.441{col 61}{space 4}-.1108572{col 74}{space 3} .2542132
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} .0351499{col 33}{space 2} .1220362{col 44}{space 1}    0.29{col 53}{space 3}0.773{col 61}{space 4}-.2043398{col 74}{space 3} .2746396
{txt}22 years and older  {c |}{col 21}{res}{space 2} .0394037{col 33}{space 2} .0708954{col 44}{space 1}    0.56{col 53}{space 3}0.578{col 61}{space 4} -.099725{col 74}{space 3} .1785323
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2} .0059669{col 33}{space 2} .0985998{col 44}{space 1}    0.06{col 53}{space 3}0.952{col 61}{space 4}-.1875302{col 74}{space 3}  .199464
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.0262186{col 33}{space 2} .0743245{col 44}{space 1}   -0.35{col 53}{space 3}0.724{col 61}{space 4}-.1720766{col 74}{space 3} .1196395
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0007101{col 33}{space 2} .0014623{col 44}{space 1}   -0.49{col 53}{space 3}0.627{col 61}{space 4}-.0035798{col 74}{space 3} .0021595
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0042012{col 33}{space 2} .0894098{col 44}{space 1}   -0.05{col 53}{space 3}0.963{col 61}{space 4}-.1796634{col 74}{space 3} .1712609
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0416434{col 33}{space 2} .0750461{col 44}{space 1}   -0.55{col 53}{space 3}0.579{col 61}{space 4}-.1889176{col 74}{space 3} .1056307
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2} -.010333{col 33}{space 2} .0669978{col 44}{space 1}   -0.15{col 53}{space 3}0.877{col 61}{space 4}-.1418127{col 74}{space 3} .1211467
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0703737{col 33}{space 2} .0911704{col 44}{space 1}    0.77{col 53}{space 3}0.440{col 61}{space 4}-.1085436{col 74}{space 3}  .249291
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0182953{col 33}{space 2} .0706796{col 44}{space 1}   -0.26{col 53}{space 3}0.796{col 61}{space 4}-.1570003{col 74}{space 3} .1204097
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .0328291{col 33}{space 2} .0729542{col 44}{space 1}    0.45{col 53}{space 3}0.653{col 61}{space 4}-.1103398{col 74}{space 3} .1759981
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2} -.085986{col 33}{space 2} .0295401{col 44}{space 1}   -2.91{col 53}{space 3}0.004{col 61}{space 4}-.1439568{col 74}{space 3}-.0280151
{txt}{space 19} {c |}
{space 13}region {c |}
{space 12}Centro  {c |}{col 21}{res}{space 2}-.0057802{col 33}{space 2} .0370114{col 44}{space 1}   -0.16{col 53}{space 3}0.876{col 61}{space 4}-.0784131{col 74}{space 3} .0668527
{txt}{space 12}Lisboa  {c |}{col 21}{res}{space 2} .0342531{col 33}{space 2} .0380314{col 44}{space 1}    0.90{col 53}{space 3}0.368{col 61}{space 4}-.0403817{col 74}{space 3} .1088878
{txt}{space 10}Alentejo  {c |}{col 21}{res}{space 2} .0889425{col 33}{space 2} .0678178{col 44}{space 1}    1.31{col 53}{space 3}0.190{col 61}{space 4}-.0441465{col 74}{space 3} .2220315
{txt}{space 11}Algarve  {c |}{col 21}{res}{space 2}-.0377344{col 33}{space 2} .0637161{col 44}{space 1}   -0.59{col 53}{space 3}0.554{col 61}{space 4} -.162774{col 74}{space 3} .0873052
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .4124743{col 33}{space 2} .1123968{col 44}{space 1}    3.67{col 53}{space 3}0.000{col 61}{space 4} .1919014{col 74}{space 3} .6330472
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store pl1
{txt}
{com}. 
. reg trust_plt i.placebo2 i.education age i.occupation gender i.region, r
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       745
                                                {txt}F(23, 721)        =  {res}     1.57
                                                {txt}Prob > F          = {res}    0.0432
                                                {txt}R-squared         = {res}    0.0391
                                                {txt}Root MSE          =    {res} .44896

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.placebo2 {c |}{col 21}{res}{space 2} .0127004{col 33}{space 2} .0344697{col 44}{space 1}    0.37{col 53}{space 3}0.713{col 61}{space 4}-.0549725{col 74}{space 3} .0803734
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0288656{col 33}{space 2} .0958632{col 44}{space 1}   -0.30{col 53}{space 3}0.763{col 61}{space 4}  -.21707{col 74}{space 3} .1593388
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0901832{col 33}{space 2}  .075545{col 44}{space 1}    1.19{col 53}{space 3}0.233{col 61}{space 4}-.0581313{col 74}{space 3} .2384977
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2}-.0071088{col 33}{space 2} .0792601{col 44}{space 1}   -0.09{col 53}{space 3}0.929{col 61}{space 4}-.1627169{col 74}{space 3} .1484993
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2}  .000875{col 33}{space 2} .0709357{col 44}{space 1}    0.01{col 53}{space 3}0.990{col 61}{space 4}-.1383902{col 74}{space 3} .1401403
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0505041{col 33}{space 2} .0882004{col 44}{space 1}   -0.57{col 53}{space 3}0.567{col 61}{space 4}-.2236644{col 74}{space 3} .1226562
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2}-.0145755{col 33}{space 2} .0991533{col 44}{space 1}   -0.15{col 53}{space 3}0.883{col 61}{space 4}-.2092392{col 74}{space 3} .1800882
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2}-.2625592{col 33}{space 2} .0886406{col 44}{space 1}   -2.96{col 53}{space 3}0.003{col 61}{space 4}-.4365838{col 74}{space 3}-.0885346
{txt}22 years and older  {c |}{col 21}{res}{space 2}-.0059984{col 33}{space 2} .0778592{col 44}{space 1}   -0.08{col 53}{space 3}0.939{col 61}{space 4}-.1588562{col 74}{space 3} .1468594
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2}-.0785468{col 33}{space 2} .1262677{col 44}{space 1}   -0.62{col 53}{space 3}0.534{col 61}{space 4}-.3264431{col 74}{space 3} .1693495
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.0119047{col 33}{space 2} .0764769{col 44}{space 1}   -0.16{col 53}{space 3}0.876{col 61}{space 4}-.1620487{col 74}{space 3} .1382393
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0014589{col 33}{space 2} .0016978{col 44}{space 1}   -0.86{col 53}{space 3}0.390{col 61}{space 4}-.0047921{col 74}{space 3} .0018743
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0394317{col 33}{space 2} .0993532{col 44}{space 1}   -0.40{col 53}{space 3}0.692{col 61}{space 4}-.2344878{col 74}{space 3} .1556244
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0962383{col 33}{space 2} .0891391{col 44}{space 1}   -1.08{col 53}{space 3}0.281{col 61}{space 4}-.2712416{col 74}{space 3} .0787649
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0749996{col 33}{space 2} .0779679{col 44}{space 1}   -0.96{col 53}{space 3}0.336{col 61}{space 4}-.2280708{col 74}{space 3} .0780717
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0424003{col 33}{space 2} .1031055{col 44}{space 1}    0.41{col 53}{space 3}0.681{col 61}{space 4}-.1600226{col 74}{space 3} .2448231
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0330547{col 33}{space 2} .0834784{col 44}{space 1}   -0.40{col 53}{space 3}0.692{col 61}{space 4}-.1969444{col 74}{space 3}  .130835
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2} .0000151{col 33}{space 2} .0828897{col 44}{space 1}    0.00{col 53}{space 3}1.000{col 61}{space 4}-.1627189{col 74}{space 3} .1627491
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.1194718{col 33}{space 2} .0346438{col 44}{space 1}   -3.45{col 53}{space 3}0.001{col 61}{space 4}-.1874866{col 74}{space 3} -.051457
{txt}{space 19} {c |}
{space 13}region {c |}
{space 12}Centro  {c |}{col 21}{res}{space 2} .0915719{col 33}{space 2} .0443813{col 44}{space 1}    2.06{col 53}{space 3}0.039{col 61}{space 4} .0044399{col 74}{space 3}  .178704
{txt}{space 12}Lisboa  {c |}{col 21}{res}{space 2} .0805467{col 33}{space 2} .0433665{col 44}{space 1}    1.86{col 53}{space 3}0.064{col 61}{space 4}-.0045931{col 74}{space 3} .1656864
{txt}{space 10}Alentejo  {c |}{col 21}{res}{space 2} .1218676{col 33}{space 2} .0723141{col 44}{space 1}    1.69{col 53}{space 3}0.092{col 61}{space 4}-.0201038{col 74}{space 3}  .263839
{txt}{space 11}Algarve  {c |}{col 21}{res}{space 2}-.0175753{col 33}{space 2} .0646158{col 44}{space 1}   -0.27{col 53}{space 3}0.786{col 61}{space 4}-.1444328{col 74}{space 3} .1092823
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .5164091{col 33}{space 2} .1330129{col 44}{space 1}    3.88{col 53}{space 3}0.000{col 61}{space 4} .2552702{col 74}{space 3}  .777548
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store pl2
{txt}
{com}. 
. reg trust_plt i.placebo3 i.education age i.occupation gender i.region, r
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       745
                                                {txt}F(23, 721)        =  {res}     1.59
                                                {txt}Prob > F          = {res}    0.0403
                                                {txt}R-squared         = {res}    0.0394
                                                {txt}Root MSE          =    {res} .44888

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.placebo3 {c |}{col 21}{res}{space 2} .0246852{col 33}{space 2} .0370738{col 44}{space 1}    0.67{col 53}{space 3}0.506{col 61}{space 4}-.0481003{col 74}{space 3} .0974707
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0287459{col 33}{space 2} .0957538{col 44}{space 1}   -0.30{col 53}{space 3}0.764{col 61}{space 4}-.2167354{col 74}{space 3} .1592436
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0900908{col 33}{space 2} .0755156{col 44}{space 1}    1.19{col 53}{space 3}0.233{col 61}{space 4}-.0581659{col 74}{space 3} .2383475
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2}-.0078203{col 33}{space 2} .0791949{col 44}{space 1}   -0.10{col 53}{space 3}0.921{col 61}{space 4}-.1633004{col 74}{space 3} .1476598
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .0029326{col 33}{space 2} .0709617{col 44}{space 1}    0.04{col 53}{space 3}0.967{col 61}{space 4}-.1363836{col 74}{space 3} .1422488
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0522636{col 33}{space 2} .0881142{col 44}{space 1}   -0.59{col 53}{space 3}0.553{col 61}{space 4}-.2252546{col 74}{space 3} .1207274
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2}-.0131465{col 33}{space 2} .0991536{col 44}{space 1}   -0.13{col 53}{space 3}0.895{col 61}{space 4}-.2078107{col 74}{space 3} .1815177
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} -.259149{col 33}{space 2} .0891338{col 44}{space 1}   -2.91{col 53}{space 3}0.004{col 61}{space 4}-.4341417{col 74}{space 3}-.0841563
{txt}22 years and older  {c |}{col 21}{res}{space 2}-.0038479{col 33}{space 2} .0779552{col 44}{space 1}   -0.05{col 53}{space 3}0.961{col 61}{space 4}-.1568941{col 74}{space 3} .1491984
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2}-.0774841{col 33}{space 2} .1262477{col 44}{space 1}   -0.61{col 53}{space 3}0.540{col 61}{space 4}-.3253411{col 74}{space 3} .1703729
{txt}No full-time edu..  {c |}{col 21}{res}{space 2}-.0116046{col 33}{space 2} .0763486{col 44}{space 1}   -0.15{col 53}{space 3}0.879{col 61}{space 4}-.1614967{col 74}{space 3} .1382876
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0014326{col 33}{space 2} .0017012{col 44}{space 1}   -0.84{col 53}{space 3}0.400{col 61}{space 4}-.0047724{col 74}{space 3} .0019073
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0399084{col 33}{space 2} .0996296{col 44}{space 1}   -0.40{col 53}{space 3}0.689{col 61}{space 4}-.2355073{col 74}{space 3} .1556904
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0951687{col 33}{space 2} .0890183{col 44}{space 1}   -1.07{col 53}{space 3}0.285{col 61}{space 4}-.2699347{col 74}{space 3} .0795972
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0752398{col 33}{space 2} .0779348{col 44}{space 1}   -0.97{col 53}{space 3}0.335{col 61}{space 4}-.2282462{col 74}{space 3} .0777665
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0409376{col 33}{space 2} .1033021{col 44}{space 1}    0.40{col 53}{space 3}0.692{col 61}{space 4}-.1618713{col 74}{space 3} .2437465
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2} -.031819{col 33}{space 2} .0835535{col 44}{space 1}   -0.38{col 53}{space 3}0.703{col 61}{space 4}-.1958563{col 74}{space 3} .1322183
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2}-.0004726{col 33}{space 2} .0828849{col 44}{space 1}   -0.01{col 53}{space 3}0.995{col 61}{space 4}-.1631972{col 74}{space 3} .1622519
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.1188017{col 33}{space 2} .0347361{col 44}{space 1}   -3.42{col 53}{space 3}0.001{col 61}{space 4}-.1869977{col 74}{space 3}-.0506056
{txt}{space 19} {c |}
{space 13}region {c |}
{space 12}Centro  {c |}{col 21}{res}{space 2} .0899531{col 33}{space 2} .0443905{col 44}{space 1}    2.03{col 53}{space 3}0.043{col 61}{space 4} .0028031{col 74}{space 3} .1771031
{txt}{space 12}Lisboa  {c |}{col 21}{res}{space 2} .0781009{col 33}{space 2}   .04354{col 44}{space 1}    1.79{col 53}{space 3}0.073{col 61}{space 4}-.0073794{col 74}{space 3} .1635811
{txt}{space 10}Alentejo  {c |}{col 21}{res}{space 2}  .125038{col 33}{space 2} .0724993{col 44}{space 1}    1.72{col 53}{space 3}0.085{col 61}{space 4}-.0172968{col 74}{space 3} .2673729
{txt}{space 11}Algarve  {c |}{col 21}{res}{space 2}-.0163379{col 33}{space 2} .0645979{col 44}{space 1}   -0.25{col 53}{space 3}0.800{col 61}{space 4}-.1431603{col 74}{space 3} .1104845
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .5044633{col 33}{space 2} .1353983{col 44}{space 1}    3.73{col 53}{space 3}0.000{col 61}{space 4} .2386412{col 74}{space 3} .7702854
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store pl3
{txt}
{com}. 
. reg trust_plt i.placebo4 i.education age i.occupation gender i.region, r
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       745
                                                {txt}F(23, 721)        =  {res}     1.58
                                                {txt}Prob > F          = {res}    0.0417
                                                {txt}R-squared         = {res}    0.0401
                                                {txt}Root MSE          =    {res} .44872

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.placebo4 {c |}{col 21}{res}{space 2} .0465699{col 33}{space 2} .0471103{col 44}{space 1}    0.99{col 53}{space 3}0.323{col 61}{space 4}-.0459199{col 74}{space 3} .1390596
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0301633{col 33}{space 2} .0957372{col 44}{space 1}   -0.32{col 53}{space 3}0.753{col 61}{space 4}-.2181202{col 74}{space 3} .1577937
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0902024{col 33}{space 2}  .075222{col 44}{space 1}    1.20{col 53}{space 3}0.231{col 61}{space 4}-.0574778{col 74}{space 3} .2378826
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} -.007497{col 33}{space 2} .0787474{col 44}{space 1}   -0.10{col 53}{space 3}0.924{col 61}{space 4}-.1620987{col 74}{space 3} .1471046
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2} .0055966{col 33}{space 2}  .071009{col 44}{space 1}    0.08{col 53}{space 3}0.937{col 61}{space 4}-.1338125{col 74}{space 3} .1450057
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0525358{col 33}{space 2}  .088103{col 44}{space 1}   -0.60{col 53}{space 3}0.551{col 61}{space 4}-.2255049{col 74}{space 3} .1204332
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2}-.0135855{col 33}{space 2} .0997142{col 44}{space 1}   -0.14{col 53}{space 3}0.892{col 61}{space 4}-.2093504{col 74}{space 3} .1821794
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2}-.2618858{col 33}{space 2} .0902674{col 44}{space 1}   -2.90{col 53}{space 3}0.004{col 61}{space 4}-.4391042{col 74}{space 3}-.0846674
{txt}22 years and older  {c |}{col 21}{res}{space 2}-.0016762{col 33}{space 2} .0780212{col 44}{space 1}   -0.02{col 53}{space 3}0.983{col 61}{space 4}-.1548521{col 74}{space 3} .1514996
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2}-.0733478{col 33}{space 2}  .126176{col 44}{space 1}   -0.58{col 53}{space 3}0.561{col 61}{space 4} -.321064{col 74}{space 3} .1743684
{txt}No full-time edu..  {c |}{col 21}{res}{space 2} -.008834{col 33}{space 2} .0759989{col 44}{space 1}   -0.12{col 53}{space 3}0.907{col 61}{space 4}-.1580395{col 74}{space 3} .1403716
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2} -.001427{col 33}{space 2} .0016931{col 44}{space 1}   -0.84{col 53}{space 3}0.400{col 61}{space 4}-.0047511{col 74}{space 3} .0018971
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2}-.0363382{col 33}{space 2} .0994336{col 44}{space 1}   -0.37{col 53}{space 3}0.715{col 61}{space 4}-.2315521{col 74}{space 3} .1588757
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.0956786{col 33}{space 2} .0891556{col 44}{space 1}   -1.07{col 53}{space 3}0.284{col 61}{space 4}-.2707142{col 74}{space 3}  .079357
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2}-.0748944{col 33}{space 2} .0779076{col 44}{space 1}   -0.96{col 53}{space 3}0.337{col 61}{space 4}-.2278472{col 74}{space 3} .0780585
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0401382{col 33}{space 2} .1029905{col 44}{space 1}    0.39{col 53}{space 3}0.697{col 61}{space 4}-.1620589{col 74}{space 3} .2423353
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0305847{col 33}{space 2} .0834847{col 44}{space 1}   -0.37{col 53}{space 3}0.714{col 61}{space 4}-.1944869{col 74}{space 3} .1333174
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2}-.0005872{col 33}{space 2} .0828383{col 44}{space 1}   -0.01{col 53}{space 3}0.994{col 61}{space 4}-.1632203{col 74}{space 3} .1620459
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.1182407{col 33}{space 2} .0346758{col 44}{space 1}   -3.41{col 53}{space 3}0.001{col 61}{space 4}-.1863184{col 74}{space 3} -.050163
{txt}{space 19} {c |}
{space 13}region {c |}
{space 12}Centro  {c |}{col 21}{res}{space 2} .0964921{col 33}{space 2}  .044624{col 44}{space 1}    2.16{col 53}{space 3}0.031{col 61}{space 4} .0088837{col 74}{space 3} .1841005
{txt}{space 12}Lisboa  {c |}{col 21}{res}{space 2} .0843573{col 33}{space 2} .0432943{col 44}{space 1}    1.95{col 53}{space 3}0.052{col 61}{space 4}-.0006407{col 74}{space 3} .1693553
{txt}{space 10}Alentejo  {c |}{col 21}{res}{space 2} .1286932{col 33}{space 2} .0727402{col 44}{space 1}    1.77{col 53}{space 3}0.077{col 61}{space 4}-.0141146{col 74}{space 3}  .271501
{txt}{space 11}Algarve  {c |}{col 21}{res}{space 2}-.0107282{col 33}{space 2} .0651527{col 44}{space 1}   -0.16{col 53}{space 3}0.869{col 61}{space 4}  -.13864{col 74}{space 3} .1171835
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .4763101{col 33}{space 2} .1405102{col 44}{space 1}    3.39{col 53}{space 3}0.001{col 61}{space 4} .2004522{col 74}{space 3} .7521681
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store pl4
{txt}
{com}. 
. reg trust_plt i.treated i.education age i.occupation gender i.region if day >= 8 & day <= 14, r   // limited bandwith
{p 0 6 2}{txt}note: 8.occupation omitted because of collinearity{p_end}

Linear regression                               Number of obs     = {res}       463
                                                {txt}F(23, 439)        =  {res}     1.28
                                                {txt}Prob > F          = {res}    0.1730
                                                {txt}R-squared         = {res}    0.0568
                                                {txt}Root MSE          =    {res}  .4523

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}          trust_plt{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}treated {c |}
{space 11}Treated  {c |}{col 21}{res}{space 2} -.113315{col 33}{space 2} .0472417{col 44}{space 1}   -2.40{col 53}{space 3}0.017{col 61}{space 4} -.206163{col 74}{space 3}-.0204669
{txt}{space 19} {c |}
{space 10}education {c |}
{space 10}15 years  {c |}{col 21}{res}{space 2}-.0750025{col 33}{space 2} .0990582{col 44}{space 1}   -0.76{col 53}{space 3}0.449{col 61}{space 4}-.2696897{col 74}{space 3} .1196847
{txt}{space 10}16 years  {c |}{col 21}{res}{space 2} .0229746{col 33}{space 2} .0931269{col 44}{space 1}    0.25{col 53}{space 3}0.805{col 61}{space 4}-.1600553{col 74}{space 3} .2060044
{txt}{space 10}17 years  {c |}{col 21}{res}{space 2} .0400125{col 33}{space 2}  .100569{col 44}{space 1}    0.40{col 53}{space 3}0.691{col 61}{space 4} -.157644{col 74}{space 3}  .237669
{txt}{space 10}18 years  {c |}{col 21}{res}{space 2}-.1798978{col 33}{space 2} .0748483{col 44}{space 1}   -2.40{col 53}{space 3}0.017{col 61}{space 4}-.3270033{col 74}{space 3}-.0327923
{txt}{space 10}19 years  {c |}{col 21}{res}{space 2}-.0657338{col 33}{space 2} .1131726{col 44}{space 1}   -0.58{col 53}{space 3}0.562{col 61}{space 4}-.2881612{col 74}{space 3} .1566936
{txt}{space 10}20 years  {c |}{col 21}{res}{space 2} .1164017{col 33}{space 2} .1493187{col 44}{space 1}    0.78{col 53}{space 3}0.436{col 61}{space 4}-.1770666{col 74}{space 3}   .40987
{txt}{space 10}21 years  {c |}{col 21}{res}{space 2} -.031202{col 33}{space 2} .1868007{col 44}{space 1}   -0.17{col 53}{space 3}0.867{col 61}{space 4}-.3983368{col 74}{space 3} .3359329
{txt}22 years and older  {c |}{col 21}{res}{space 2}  .088001{col 33}{space 2} .1102577{col 44}{space 1}    0.80{col 53}{space 3}0.425{col 61}{space 4}-.1286975{col 74}{space 3} .3046994
{txt}{space 4}Still studying  {c |}{col 21}{res}{space 2}-.0355997{col 33}{space 2}  .137215{col 44}{space 1}   -0.26{col 53}{space 3}0.795{col 61}{space 4}-.3052796{col 74}{space 3} .2340802
{txt}No full-time edu..  {c |}{col 21}{res}{space 2} .1119653{col 33}{space 2} .1391745{col 44}{space 1}    0.80{col 53}{space 3}0.422{col 61}{space 4}-.1615659{col 74}{space 3} .3854965
{txt}{space 19} {c |}
{space 16}age {c |}{col 21}{res}{space 2}-.0003316{col 33}{space 2} .0021917{col 44}{space 1}   -0.15{col 53}{space 3}0.880{col 61}{space 4} -.004639{col 74}{space 3} .0039759
{txt}{space 19} {c |}
{space 9}occupation {c |}
Managers (10 to..)  {c |}{col 21}{res}{space 2} .0340686{col 33}{space 2} .1223671{col 44}{space 1}    0.28{col 53}{space 3}0.781{col 61}{space 4}-.2064296{col 74}{space 3} .2745668
{txt}Other white col..)  {c |}{col 21}{res}{space 2}-.1300879{col 33}{space 2} .0948081{col 44}{space 1}   -1.37{col 53}{space 3}0.171{col 61}{space 4}-.3164221{col 74}{space 3} .0562463
{txt}Manual workers ..)  {c |}{col 21}{res}{space 2} .0010111{col 33}{space 2} .0901224{col 44}{space 1}    0.01{col 53}{space 3}0.991{col 61}{space 4}-.1761138{col 74}{space 3}  .178136
{txt}House persons (..)  {c |}{col 21}{res}{space 2} .0198593{col 33}{space 2}  .140799{col 44}{space 1}    0.14{col 53}{space 3}0.888{col 61}{space 4}-.2568645{col 74}{space 3} .2965831
{txt}Unemployed (3 i..)  {c |}{col 21}{res}{space 2}-.0667403{col 33}{space 2}  .094501{col 44}{space 1}   -0.71{col 53}{space 3}0.480{col 61}{space 4}-.2524709{col 74}{space 3} .1189902
{txt}Retired (4 in V..)  {c |}{col 21}{res}{space 2}-.1044447{col 33}{space 2} .1035971{col 44}{space 1}   -1.01{col 53}{space 3}0.314{col 61}{space 4}-.3080527{col 74}{space 3} .0991633
{txt}Students (2 in ..)  {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 19} {c |}
{space 13}gender {c |}{col 21}{res}{space 2}-.0353181{col 33}{space 2} .0430954{col 44}{space 1}   -0.82{col 53}{space 3}0.413{col 61}{space 4} -.120017{col 74}{space 3} .0493809
{txt}{space 19} {c |}
{space 13}region {c |}
{space 12}Centro  {c |}{col 21}{res}{space 2} .0287465{col 33}{space 2}  .057973{col 44}{space 1}    0.50{col 53}{space 3}0.620{col 61}{space 4}-.0851926{col 74}{space 3} .1426857
{txt}{space 12}Lisboa  {c |}{col 21}{res}{space 2} .0841004{col 33}{space 2} .0550109{col 44}{space 1}    1.53{col 53}{space 3}0.127{col 61}{space 4} -.024017{col 74}{space 3} .1922178
{txt}{space 10}Alentejo  {c |}{col 21}{res}{space 2} .0449079{col 33}{space 2} .1070085{col 44}{space 1}    0.42{col 53}{space 3}0.675{col 61}{space 4}-.1654047{col 74}{space 3} .2552206
{txt}{space 11}Algarve  {c |}{col 21}{res}{space 2} .0075619{col 33}{space 2} .0924483{col 44}{space 1}    0.08{col 53}{space 3}0.935{col 61}{space 4}-.1741343{col 74}{space 3} .1892581
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .4015242{col 33}{space 2} .1580572{col 44}{space 1}    2.54{col 53}{space 3}0.011{col 61}{space 4} .0908813{col 74}{space 3} .7121672
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store pl5
{txt}
{com}. 
. * Table of placebos
. esttab  pl1 pl2 pl3 pl4 pl5 using TableA7.tex, replace se star(+ 0.10 * 0.05 ** 0.01 *** 0.001) label booktabs nobaselevels ///
> mtitles ("Median (with Treated)" "Median (without treated)" "6th Day" "5th day" "Reduced bandwidth") ///
> order (1.placebo 1.placebo2 1.placebo3 1.placebo4 1.treated) ///
> coeflabels(1.placebo "Placebo 1" 1.placebo2 "Placebo 2" 1.placebo3 "Placebo 3" 1.placebo4 "Placebo 4" 1.treated "Treated") ///
> indicate("Region Fixed Effect = *.region", labels("\checkmark" "")) ///
> title(Placebo Tests for Political Trust (Average Marginal Effects Reported) \label{c -(}tab:placebo_trust{c )-})
{res}{txt}(note: file TableA7.tex not found)
(output written to {browse  `"TableA7.tex"'})

{com}. 
. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A6 ***
.                                                                                                         ******************
. 
. reg econ_evals i.placebo education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,022
{txt}{hline 13}{c +}{hline 34}   F(5, 1016)      = {res}     0.59
{txt}       Model {c |} {res} 1.00681545         5   .20136309   {txt}Prob > F        ={res}    0.7040
{txt}    Residual {c |} {res} 343.975572     1,016  .338558634   {txt}R-squared       ={res}    0.0029
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0020
{txt}       Total {c |} {res} 344.982387     1,021  .337886765   {txt}Root MSE        =   {res} .58186

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.placebo {c |}{col 14}{res}{space 2}-.0326758{col 26}{space 2} .0409075{col 37}{space 1}   -0.80{col 46}{space 3}0.425{col 54}{space 4}-.1129487{col 67}{space 3} .0475972
{txt}{space 3}education {c |}{col 14}{res}{space 2} -.000321{col 26}{space 2} .0058178{col 37}{space 1}   -0.06{col 46}{space 3}0.956{col 54}{space 4}-.0117374{col 67}{space 3} .0110953
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0000645{col 26}{space 2} .0011295{col 37}{space 1}    0.06{col 46}{space 3}0.954{col 54}{space 4}-.0021518{col 67}{space 3} .0022809
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0070375{col 26}{space 2} .0095968{col 37}{space 1}   -0.73{col 46}{space 3}0.464{col 54}{space 4}-.0258693{col 67}{space 3} .0117943
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0509783{col 26}{space 2} .0365959{col 37}{space 1}   -1.39{col 46}{space 3}0.164{col 54}{space 4}-.1227904{col 67}{space 3} .0208339
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.658049{col 26}{space 2} .0990938{col 37}{space 1}   16.73{col 46}{space 3}0.000{col 54}{space 4} 1.463597{col 67}{space 3} 1.852501
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     1,022
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.placebo {c |}{col 14}{res}{space 2}-.0326758{col 26}{space 2} .0409075{col 37}{space 1}   -0.80{col 46}{space 3}0.425{col 54}{space 4}-.1129487{col 67}{space 3} .0475972
{txt}{space 3}education {c |}{col 14}{res}{space 2} -.000321{col 26}{space 2} .0058178{col 37}{space 1}   -0.06{col 46}{space 3}0.956{col 54}{space 4}-.0117374{col 67}{space 3} .0110953
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0000645{col 26}{space 2} .0011295{col 37}{space 1}    0.06{col 46}{space 3}0.954{col 54}{space 4}-.0021518{col 67}{space 3} .0022809
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0070375{col 26}{space 2} .0095968{col 37}{space 1}   -0.73{col 46}{space 3}0.464{col 54}{space 4}-.0258693{col 67}{space 3} .0117943
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0509783{col 26}{space 2} .0365959{col 37}{space 1}   -1.39{col 46}{space 3}0.164{col 54}{space 4}-.1227904{col 67}{space 3} .0208339
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store evals_pl1
{txt}
{com}. 
. reg econ_evals i.placebo2 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       784
{txt}{hline 13}{c +}{hline 34}   F(5, 778)       = {res}     0.67
{txt}       Model {c |} {res} 1.15638583         5  .231277166   {txt}Prob > F        ={res}    0.6478
{txt}    Residual {c |} {res} 269.369124       778  .346232808   {txt}R-squared       ={res}    0.0043
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0021
{txt}       Total {c |} {res}  270.52551       783  .345498736   {txt}Root MSE        =   {res} .58842

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo2 {c |}{col 14}{res}{space 2}-.0044315{col 26}{space 2}  .043678{col 37}{space 1}   -0.10{col 46}{space 3}0.919{col 54}{space 4}-.0901721{col 67}{space 3} .0813092
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0023123{col 26}{space 2} .0065973{col 37}{space 1}   -0.35{col 46}{space 3}0.726{col 54}{space 4}-.0152628{col 67}{space 3} .0106383
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009184{col 26}{space 2} .0013321{col 37}{space 1}   -0.69{col 46}{space 3}0.491{col 54}{space 4}-.0035334{col 67}{space 3} .0016966
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0056171{col 26}{space 2}  .011595{col 37}{space 1}   -0.48{col 46}{space 3}0.628{col 54}{space 4}-.0283783{col 67}{space 3} .0171441
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0615351{col 26}{space 2} .0425639{col 37}{space 1}   -1.45{col 46}{space 3}0.149{col 54}{space 4}-.1450887{col 67}{space 3} .0220185
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  1.72611{col 26}{space 2} .1099781{col 37}{space 1}   15.70{col 46}{space 3}0.000{col 54}{space 4} 1.510221{col 67}{space 3} 1.941998
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       784
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo2 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo2 {c |}{col 14}{res}{space 2}-.0044315{col 26}{space 2}  .043678{col 37}{space 1}   -0.10{col 46}{space 3}0.919{col 54}{space 4}-.0901721{col 67}{space 3} .0813092
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0023123{col 26}{space 2} .0065973{col 37}{space 1}   -0.35{col 46}{space 3}0.726{col 54}{space 4}-.0152628{col 67}{space 3} .0106383
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009184{col 26}{space 2} .0013321{col 37}{space 1}   -0.69{col 46}{space 3}0.491{col 54}{space 4}-.0035334{col 67}{space 3} .0016966
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0056171{col 26}{space 2}  .011595{col 37}{space 1}   -0.48{col 46}{space 3}0.628{col 54}{space 4}-.0283783{col 67}{space 3} .0171441
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0615351{col 26}{space 2} .0425639{col 37}{space 1}   -1.45{col 46}{space 3}0.149{col 54}{space 4}-.1450887{col 67}{space 3} .0220185
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store evals_pl2
{txt}
{com}. 
. reg econ_evals i.placebo3 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       784
{txt}{hline 13}{c +}{hline 34}   F(5, 778)       = {res}     0.68
{txt}       Model {c |} {res} 1.18360632         5  .236721264   {txt}Prob > F        ={res}    0.6358
{txt}    Residual {c |} {res} 269.341904       778   .34619782   {txt}R-squared       ={res}    0.0044
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0020
{txt}       Total {c |} {res}  270.52551       783  .345498736   {txt}Root MSE        =   {res} .58839

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo3 {c |}{col 14}{res}{space 2}-.0141156{col 26}{space 2} .0473364{col 37}{space 1}   -0.30{col 46}{space 3}0.766{col 54}{space 4}-.1070378{col 67}{space 3} .0788066
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0024002{col 26}{space 2} .0066041{col 37}{space 1}   -0.36{col 46}{space 3}0.716{col 54}{space 4}-.0153642{col 67}{space 3} .0105638
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009372{col 26}{space 2}  .001332{col 37}{space 1}   -0.70{col 46}{space 3}0.482{col 54}{space 4}-.0035519{col 67}{space 3} .0016774
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0056481{col 26}{space 2} .0115829{col 37}{space 1}   -0.49{col 46}{space 3}0.626{col 54}{space 4}-.0283856{col 67}{space 3} .0170894
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0617677{col 26}{space 2} .0425697{col 37}{space 1}   -1.45{col 46}{space 3}0.147{col 54}{space 4}-.1453328{col 67}{space 3} .0217974
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.735376{col 26}{space 2} .1125795{col 37}{space 1}   15.41{col 46}{space 3}0.000{col 54}{space 4}  1.51438{col 67}{space 3} 1.956371
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       784
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo3 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo3 {c |}{col 14}{res}{space 2}-.0141156{col 26}{space 2} .0473364{col 37}{space 1}   -0.30{col 46}{space 3}0.766{col 54}{space 4}-.1070378{col 67}{space 3} .0788066
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0024002{col 26}{space 2} .0066041{col 37}{space 1}   -0.36{col 46}{space 3}0.716{col 54}{space 4}-.0153642{col 67}{space 3} .0105638
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009372{col 26}{space 2}  .001332{col 37}{space 1}   -0.70{col 46}{space 3}0.482{col 54}{space 4}-.0035519{col 67}{space 3} .0016774
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0056481{col 26}{space 2} .0115829{col 37}{space 1}   -0.49{col 46}{space 3}0.626{col 54}{space 4}-.0283856{col 67}{space 3} .0170894
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0617677{col 26}{space 2} .0425697{col 37}{space 1}   -1.45{col 46}{space 3}0.147{col 54}{space 4}-.1453328{col 67}{space 3} .0217974
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store evals_pl3
{txt}
{com}. 
. reg econ_evals i.placebo4 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       784
{txt}{hline 13}{c +}{hline 34}   F(5, 778)       = {res}     0.67
{txt}       Model {c |} {res} 1.16762242         5  .233524484   {txt}Prob > F        ={res}    0.6429
{txt}    Residual {c |} {res} 269.357888       778  .346218365   {txt}R-squared       ={res}    0.0043
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0021
{txt}       Total {c |} {res}  270.52551       783  .345498736   {txt}Root MSE        =   {res}  .5884

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo4 {c |}{col 14}{res}{space 2}-.0124397{col 26}{space 2}  .060165{col 37}{space 1}   -0.21{col 46}{space 3}0.836{col 54}{space 4}-.1305447{col 67}{space 3} .1056654
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0024384{col 26}{space 2} .0066275{col 37}{space 1}   -0.37{col 46}{space 3}0.713{col 54}{space 4}-.0154483{col 67}{space 3} .0105714
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009167{col 26}{space 2} .0013291{col 37}{space 1}   -0.69{col 46}{space 3}0.491{col 54}{space 4}-.0035258{col 67}{space 3} .0016923
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0056114{col 26}{space 2} .0115822{col 37}{space 1}   -0.48{col 46}{space 3}0.628{col 54}{space 4}-.0283476{col 67}{space 3} .0171247
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0617347{col 26}{space 2} .0425769{col 37}{space 1}   -1.45{col 46}{space 3}0.147{col 54}{space 4}-.1453138{col 67}{space 3} .0218445
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.734645{col 26}{space 2} .1194707{col 37}{space 1}   14.52{col 46}{space 3}0.000{col 54}{space 4} 1.500122{col 67}{space 3} 1.969168
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       784
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo4 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo4 {c |}{col 14}{res}{space 2}-.0124397{col 26}{space 2}  .060165{col 37}{space 1}   -0.21{col 46}{space 3}0.836{col 54}{space 4}-.1305447{col 67}{space 3} .1056654
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0024384{col 26}{space 2} .0066275{col 37}{space 1}   -0.37{col 46}{space 3}0.713{col 54}{space 4}-.0154483{col 67}{space 3} .0105714
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0009167{col 26}{space 2} .0013291{col 37}{space 1}   -0.69{col 46}{space 3}0.491{col 54}{space 4}-.0035258{col 67}{space 3} .0016923
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0056114{col 26}{space 2} .0115822{col 37}{space 1}   -0.48{col 46}{space 3}0.628{col 54}{space 4}-.0283476{col 67}{space 3} .0171247
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0617347{col 26}{space 2} .0425769{col 37}{space 1}   -1.45{col 46}{space 3}0.147{col 54}{space 4}-.1453138{col 67}{space 3} .0218445
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store evals_pl4
{txt}
{com}. 
. reg econ_evals i.treated education age occupation gender if day >= 8 & day <= 14 // limited bandwith

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       475
{txt}{hline 13}{c +}{hline 34}   F(5, 469)       = {res}     1.11
{txt}       Model {c |} {res} 1.82791756         5  .365583512   {txt}Prob > F        ={res}    0.3534
{txt}    Residual {c |} {res} 154.277346       469  .328949564   {txt}R-squared       ={res}    0.0117
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0012
{txt}       Total {c |} {res} 156.105263       474  .329335998   {txt}Root MSE        =   {res} .57354

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1145902{col 26}{space 2} .0635362{col 37}{space 1}   -1.80{col 46}{space 3}0.072{col 54}{space 4}-.2394412{col 67}{space 3} .0102607
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0080157{col 26}{space 2} .0090728{col 37}{space 1}   -0.88{col 46}{space 3}0.377{col 54}{space 4}-.0258441{col 67}{space 3} .0098126
{txt}{space 9}age {c |}{col 14}{res}{space 2} -.001885{col 26}{space 2} .0017691{col 37}{space 1}   -1.07{col 46}{space 3}0.287{col 54}{space 4}-.0053614{col 67}{space 3} .0015914
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} -.004469{col 26}{space 2}  .013707{col 37}{space 1}   -0.33{col 46}{space 3}0.745{col 54}{space 4}-.0314037{col 67}{space 3} .0224657
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0527967{col 26}{space 2}  .052881{col 37}{space 1}   -1.00{col 46}{space 3}0.319{col 54}{space 4}-.1567097{col 67}{space 3} .0511162
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.785578{col 26}{space 2} .1356644{col 37}{space 1}   13.16{col 46}{space 3}0.000{col 54}{space 4} 1.518992{col 67}{space 3} 2.052163
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       475
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.treated education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1145902{col 26}{space 2} .0635362{col 37}{space 1}   -1.80{col 46}{space 3}0.072{col 54}{space 4}-.2394412{col 67}{space 3} .0102607
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0080157{col 26}{space 2} .0090728{col 37}{space 1}   -0.88{col 46}{space 3}0.377{col 54}{space 4}-.0258441{col 67}{space 3} .0098126
{txt}{space 9}age {c |}{col 14}{res}{space 2} -.001885{col 26}{space 2} .0017691{col 37}{space 1}   -1.07{col 46}{space 3}0.287{col 54}{space 4}-.0053614{col 67}{space 3} .0015914
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} -.004469{col 26}{space 2}  .013707{col 37}{space 1}   -0.33{col 46}{space 3}0.745{col 54}{space 4}-.0314037{col 67}{space 3} .0224657
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0527967{col 26}{space 2}  .052881{col 37}{space 1}   -1.00{col 46}{space 3}0.319{col 54}{space 4}-.1567097{col 67}{space 3} .0511162
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store evals_pl5
{txt}
{com}. 
. reg econ_index i.placebo education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       729
{txt}{hline 13}{c +}{hline 34}   F(5, 723)       = {res}     1.15
{txt}       Model {c |} {res} 2.45104711         5  .490209421   {txt}Prob > F        ={res}    0.3303
{txt}    Residual {c |} {res} 307.057869       723  .424699681   {txt}R-squared       ={res}    0.0079
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0011
{txt}       Total {c |} {res} 309.508916       728   .42514961   {txt}Root MSE        =   {res} .65169

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.placebo {c |}{col 14}{res}{space 2} .0491688{col 26}{space 2} .0539628{col 37}{space 1}    0.91{col 46}{space 3}0.363{col 54}{space 4}-.0567737{col 67}{space 3} .1551114
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0035011{col 26}{space 2} .0076253{col 37}{space 1}    0.46{col 46}{space 3}0.646{col 54}{space 4}-.0114693{col 67}{space 3} .0184715
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0023916{col 26}{space 2} .0015192{col 37}{space 1}   -1.57{col 46}{space 3}0.116{col 54}{space 4}-.0053742{col 67}{space 3}  .000591
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0031251{col 26}{space 2} .0129528{col 37}{space 1}    0.24{col 46}{space 3}0.809{col 54}{space 4}-.0223046{col 67}{space 3} .0285548
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0111957{col 26}{space 2} .0485739{col 37}{space 1}   -0.23{col 46}{space 3}0.818{col 54}{space 4}-.1065585{col 67}{space 3} .0841671
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.309703{col 26}{space 2} .1301293{col 37}{space 1}   10.06{col 46}{space 3}0.000{col 54}{space 4} 1.054227{col 67}{space 3}  1.56518
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       729
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.placebo {c |}{col 14}{res}{space 2} .0491688{col 26}{space 2} .0539628{col 37}{space 1}    0.91{col 46}{space 3}0.363{col 54}{space 4}-.0567737{col 67}{space 3} .1551114
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0035011{col 26}{space 2} .0076253{col 37}{space 1}    0.46{col 46}{space 3}0.646{col 54}{space 4}-.0114693{col 67}{space 3} .0184715
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0023916{col 26}{space 2} .0015192{col 37}{space 1}   -1.57{col 46}{space 3}0.116{col 54}{space 4}-.0053742{col 67}{space 3}  .000591
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0031251{col 26}{space 2} .0129528{col 37}{space 1}    0.24{col 46}{space 3}0.809{col 54}{space 4}-.0223046{col 67}{space 3} .0285548
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0111957{col 26}{space 2} .0485739{col 37}{space 1}   -0.23{col 46}{space 3}0.818{col 54}{space 4}-.1065585{col 67}{space 3} .0841671
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store index_pl1
{txt}
{com}. 
. reg econ_index i.placebo2 education age occupation gender 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       557
{txt}{hline 13}{c +}{hline 34}   F(5, 551)       = {res}     2.73
{txt}       Model {c |} {res} 6.53239128         5  1.30647826   {txt}Prob > F        ={res}    0.0190
{txt}    Residual {c |} {res} 263.776406       551   .47872306   {txt}R-squared       ={res}    0.0242
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0153
{txt}       Total {c |} {res} 270.308797       556  .486166901   {txt}Root MSE        =   {res}  .6919

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo2 {c |}{col 14}{res}{space 2} .1280079{col 26}{space 2} .0607474{col 37}{space 1}    2.11{col 46}{space 3}0.036{col 54}{space 4}  .008683{col 67}{space 3} .2473327
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0016368{col 26}{space 2} .0090665{col 37}{space 1}   -0.18{col 46}{space 3}0.857{col 54}{space 4}-.0194461{col 67}{space 3} .0161724
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0046036{col 26}{space 2} .0018858{col 37}{space 1}   -2.44{col 46}{space 3}0.015{col 54}{space 4}-.0083077{col 67}{space 3}-.0008994
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0097424{col 26}{space 2} .0165459{col 37}{space 1}    0.59{col 46}{space 3}0.556{col 54}{space 4}-.0227584{col 67}{space 3} .0422432
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0570896{col 26}{space 2} .0594845{col 37}{space 1}   -0.96{col 46}{space 3}0.338{col 54}{space 4}-.1739336{col 67}{space 3} .0597545
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.483126{col 26}{space 2} .1523551{col 37}{space 1}    9.73{col 46}{space 3}0.000{col 54}{space 4} 1.183858{col 67}{space 3} 1.782394
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       557
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo2 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo2 {c |}{col 14}{res}{space 2} .1280079{col 26}{space 2} .0607474{col 37}{space 1}    2.11{col 46}{space 3}0.036{col 54}{space 4}  .008683{col 67}{space 3} .2473327
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0016368{col 26}{space 2} .0090665{col 37}{space 1}   -0.18{col 46}{space 3}0.857{col 54}{space 4}-.0194461{col 67}{space 3} .0161724
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0046036{col 26}{space 2} .0018858{col 37}{space 1}   -2.44{col 46}{space 3}0.015{col 54}{space 4}-.0083077{col 67}{space 3}-.0008994
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0097424{col 26}{space 2} .0165459{col 37}{space 1}    0.59{col 46}{space 3}0.556{col 54}{space 4}-.0227584{col 67}{space 3} .0422432
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0570896{col 26}{space 2} .0594845{col 37}{space 1}   -0.96{col 46}{space 3}0.338{col 54}{space 4}-.1739336{col 67}{space 3} .0597545
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store index_pl2
{txt}
{com}. 
. reg econ_index i.placebo3 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       557
{txt}{hline 13}{c +}{hline 34}   F(5, 551)       = {res}     2.23
{txt}       Model {c |} {res} 5.36865975         5  1.07373195   {txt}Prob > F        ={res}    0.0497
{txt}    Residual {c |} {res} 264.940137       551  .480835095   {txt}R-squared       ={res}    0.0199
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0110
{txt}       Total {c |} {res} 270.308797       556  .486166901   {txt}Root MSE        =   {res} .69342

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo3 {c |}{col 14}{res}{space 2} .0940254{col 26}{space 2} .0664757{col 37}{space 1}    1.41{col 46}{space 3}0.158{col 54}{space 4}-.0365513{col 67}{space 3} .2246021
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0006333{col 26}{space 2} .0090897{col 37}{space 1}   -0.07{col 46}{space 3}0.944{col 54}{space 4} -.018488{col 67}{space 3} .0172215
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0047247{col 26}{space 2} .0018894{col 37}{space 1}   -2.50{col 46}{space 3}0.013{col 54}{space 4}-.0084361{col 67}{space 3}-.0010133
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0079539{col 26}{space 2} .0165504{col 37}{space 1}    0.48{col 46}{space 3}0.631{col 54}{space 4}-.0245557{col 67}{space 3} .0404636
{txt}{space 6}gender {c |}{col 14}{res}{space 2}  -.05361{col 26}{space 2} .0596171{col 37}{space 1}   -0.90{col 46}{space 3}0.369{col 54}{space 4}-.1707146{col 67}{space 3} .0634945
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.498401{col 26}{space 2} .1572214{col 37}{space 1}    9.53{col 46}{space 3}0.000{col 54}{space 4} 1.189574{col 67}{space 3} 1.807228
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       557
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo3 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo3 {c |}{col 14}{res}{space 2} .0940254{col 26}{space 2} .0664757{col 37}{space 1}    1.41{col 46}{space 3}0.158{col 54}{space 4}-.0365513{col 67}{space 3} .2246021
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0006333{col 26}{space 2} .0090897{col 37}{space 1}   -0.07{col 46}{space 3}0.944{col 54}{space 4} -.018488{col 67}{space 3} .0172215
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0047247{col 26}{space 2} .0018894{col 37}{space 1}   -2.50{col 46}{space 3}0.013{col 54}{space 4}-.0084361{col 67}{space 3}-.0010133
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0079539{col 26}{space 2} .0165504{col 37}{space 1}    0.48{col 46}{space 3}0.631{col 54}{space 4}-.0245557{col 67}{space 3} .0404636
{txt}{space 6}gender {c |}{col 14}{res}{space 2}  -.05361{col 26}{space 2} .0596171{col 37}{space 1}   -0.90{col 46}{space 3}0.369{col 54}{space 4}-.1707146{col 67}{space 3} .0634945
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store index_pl3
{txt}
{com}. 
. reg econ_index i.placebo4 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       557
{txt}{hline 13}{c +}{hline 34}   F(5, 551)       = {res}     2.07
{txt}       Model {c |} {res} 4.99393022         5  .998786044   {txt}Prob > F        ={res}    0.0671
{txt}    Residual {c |} {res} 265.314867       551  .481515185   {txt}R-squared       ={res}    0.0185
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0096
{txt}       Total {c |} {res} 270.308797       556  .486166901   {txt}Root MSE        =   {res} .69391

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo4 {c |}{col 14}{res}{space 2} .0899753{col 26}{space 2} .0814743{col 37}{space 1}    1.10{col 46}{space 3}0.270{col 54}{space 4}-.0700629{col 67}{space 3} .2500135
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0001384{col 26}{space 2}  .009133{col 37}{space 1}   -0.02{col 46}{space 3}0.988{col 54}{space 4}-.0180781{col 67}{space 3} .0178013
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0048297{col 26}{space 2} .0018872{col 37}{space 1}   -2.56{col 46}{space 3}0.011{col 54}{space 4}-.0085367{col 67}{space 3}-.0011228
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0072964{col 26}{space 2}  .016559{col 37}{space 1}    0.44{col 46}{space 3}0.660{col 54}{space 4}-.0252301{col 67}{space 3}  .039823
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0528932{col 26}{space 2} .0596831{col 37}{space 1}   -0.89{col 46}{space 3}0.376{col 54}{space 4}-.1701275{col 67}{space 3} .0643411
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.496773{col 26}{space 2} .1654894{col 37}{space 1}    9.04{col 46}{space 3}0.000{col 54}{space 4} 1.171706{col 67}{space 3} 1.821841
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       557
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo4 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo4 {c |}{col 14}{res}{space 2} .0899753{col 26}{space 2} .0814743{col 37}{space 1}    1.10{col 46}{space 3}0.270{col 54}{space 4}-.0700629{col 67}{space 3} .2500135
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0001384{col 26}{space 2}  .009133{col 37}{space 1}   -0.02{col 46}{space 3}0.988{col 54}{space 4}-.0180781{col 67}{space 3} .0178013
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0048297{col 26}{space 2} .0018872{col 37}{space 1}   -2.56{col 46}{space 3}0.011{col 54}{space 4}-.0085367{col 67}{space 3}-.0011228
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0072964{col 26}{space 2}  .016559{col 37}{space 1}    0.44{col 46}{space 3}0.660{col 54}{space 4}-.0252301{col 67}{space 3}  .039823
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0528932{col 26}{space 2} .0596831{col 37}{space 1}   -0.89{col 46}{space 3}0.376{col 54}{space 4}-.1701275{col 67}{space 3} .0643411
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store index_pl4
{txt}
{com}. 
. reg econ_index i.treated education age occupation gender if day >= 8 & day <= 14 // limited bandwith

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       324
{txt}{hline 13}{c +}{hline 34}   F(5, 318)       = {res}     3.06
{txt}       Model {c |} {res} 7.76527552         5   1.5530551   {txt}Prob > F        ={res}    0.0103
{txt}    Residual {c |} {res} 161.370527       318  .507454487   {txt}R-squared       ={res}    0.0459
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0309
{txt}       Total {c |} {res} 169.135802       323  .523640255   {txt}Root MSE        =   {res} .71236

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.2731561{col 26}{space 2} .0937996{col 37}{space 1}   -2.91{col 46}{space 3}0.004{col 54}{space 4}-.4577022{col 67}{space 3}-.0886099
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0044077{col 26}{space 2} .0134462{col 37}{space 1}   -0.33{col 46}{space 3}0.743{col 54}{space 4}-.0308625{col 67}{space 3}  .022047
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0081423{col 26}{space 2} .0027362{col 37}{space 1}   -2.98{col 46}{space 3}0.003{col 54}{space 4}-.0135257{col 67}{space 3}-.0027589
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0114444{col 26}{space 2} .0206509{col 37}{space 1}    0.55{col 46}{space 3}0.580{col 54}{space 4}-.0291852{col 67}{space 3}  .052074
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0155846{col 26}{space 2} .0796921{col 37}{space 1}   -0.20{col 46}{space 3}0.845{col 54}{space 4} -.172375{col 67}{space 3} .1412058
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.743091{col 26}{space 2} .2008458{col 37}{space 1}    8.68{col 46}{space 3}0.000{col 54}{space 4} 1.347936{col 67}{space 3} 2.138245
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       324
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.treated education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.2731561{col 26}{space 2} .0937996{col 37}{space 1}   -2.91{col 46}{space 3}0.004{col 54}{space 4}-.4577022{col 67}{space 3}-.0886099
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0044077{col 26}{space 2} .0134462{col 37}{space 1}   -0.33{col 46}{space 3}0.743{col 54}{space 4}-.0308625{col 67}{space 3}  .022047
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0081423{col 26}{space 2} .0027362{col 37}{space 1}   -2.98{col 46}{space 3}0.003{col 54}{space 4}-.0135257{col 67}{space 3}-.0027589
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0114444{col 26}{space 2} .0206509{col 37}{space 1}    0.55{col 46}{space 3}0.580{col 54}{space 4}-.0291852{col 67}{space 3}  .052074
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0155846{col 26}{space 2} .0796921{col 37}{space 1}   -0.20{col 46}{space 3}0.845{col 54}{space 4} -.172375{col 67}{space 3} .1412058
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store index_pl5
{txt}
{com}. 
. reg econ_expec i.placebo education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       967
{txt}{hline 13}{c +}{hline 34}   F(5, 961)       = {res}     3.41
{txt}       Model {c |} {res} 6.77574437         5  1.35514887   {txt}Prob > F        ={res}    0.0047
{txt}    Residual {c |} {res} 382.316293       961   .39783173   {txt}R-squared       ={res}    0.0174
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0123
{txt}       Total {c |} {res} 389.092037       966  .402786788   {txt}Root MSE        =   {res} .63074

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.placebo {c |}{col 14}{res}{space 2} .1016396{col 26}{space 2} .0456956{col 37}{space 1}    2.22{col 46}{space 3}0.026{col 54}{space 4}  .011965{col 67}{space 3} .1913142
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0067643{col 26}{space 2}  .006525{col 37}{space 1}   -1.04{col 46}{space 3}0.300{col 54}{space 4}-.0195693{col 67}{space 3} .0060406
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0034262{col 26}{space 2} .0012853{col 37}{space 1}   -2.67{col 46}{space 3}0.008{col 54}{space 4}-.0059486{col 67}{space 3}-.0009039
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0061154{col 26}{space 2}  .010709{col 37}{space 1}   -0.57{col 46}{space 3}0.568{col 54}{space 4}-.0271311{col 67}{space 3} .0149003
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0160837{col 26}{space 2} .0407378{col 37}{space 1}    0.39{col 46}{space 3}0.693{col 54}{space 4}-.0638615{col 67}{space 3} .0960289
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.525799{col 26}{space 2} .1108863{col 37}{space 1}   13.76{col 46}{space 3}0.000{col 54}{space 4} 1.308192{col 67}{space 3} 1.743407
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       967
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}1.placebo {c |}{col 14}{res}{space 2} .1016396{col 26}{space 2} .0456956{col 37}{space 1}    2.22{col 46}{space 3}0.026{col 54}{space 4}  .011965{col 67}{space 3} .1913142
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0067643{col 26}{space 2}  .006525{col 37}{space 1}   -1.04{col 46}{space 3}0.300{col 54}{space 4}-.0195693{col 67}{space 3} .0060406
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0034262{col 26}{space 2} .0012853{col 37}{space 1}   -2.67{col 46}{space 3}0.008{col 54}{space 4}-.0059486{col 67}{space 3}-.0009039
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0061154{col 26}{space 2}  .010709{col 37}{space 1}   -0.57{col 46}{space 3}0.568{col 54}{space 4}-.0271311{col 67}{space 3} .0149003
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0160837{col 26}{space 2} .0407378{col 37}{space 1}    0.39{col 46}{space 3}0.693{col 54}{space 4}-.0638615{col 67}{space 3} .0960289
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store expec_pl1
{txt}
{com}. 
. reg econ_expec i.placebo2 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       741
{txt}{hline 13}{c +}{hline 34}   F(5, 735)       = {res}     6.09
{txt}       Model {c |} {res} 12.7131384         5  2.54262767   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 307.095229       735  .417816638   {txt}R-squared       ={res}    0.0398
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0332
{txt}       Total {c |} {res} 319.808367       740  .432173469   {txt}Root MSE        =   {res} .64639

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo2 {c |}{col 14}{res}{space 2} .1653229{col 26}{space 2} .0494267{col 37}{space 1}    3.34{col 46}{space 3}0.001{col 54}{space 4} .0682886{col 67}{space 3} .2623572
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0118724{col 26}{space 2} .0075021{col 37}{space 1}   -1.58{col 46}{space 3}0.114{col 54}{space 4}-.0266005{col 67}{space 3} .0028557
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0057712{col 26}{space 2}  .001532{col 37}{space 1}   -3.77{col 46}{space 3}0.000{col 54}{space 4}-.0087787{col 67}{space 3}-.0027636
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0021777{col 26}{space 2} .0131477{col 37}{space 1}    0.17{col 46}{space 3}0.868{col 54}{space 4}-.0236338{col 67}{space 3} .0279892
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0161652{col 26}{space 2} .0480323{col 37}{space 1}   -0.34{col 46}{space 3}0.737{col 54}{space 4}-.1104621{col 67}{space 3} .0781317
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.673695{col 26}{space 2} .1250275{col 37}{space 1}   13.39{col 46}{space 3}0.000{col 54}{space 4} 1.428241{col 67}{space 3} 1.919148
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       741
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo2 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo2 {c |}{col 14}{res}{space 2} .1653229{col 26}{space 2} .0494267{col 37}{space 1}    3.34{col 46}{space 3}0.001{col 54}{space 4} .0682886{col 67}{space 3} .2623572
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0118724{col 26}{space 2} .0075021{col 37}{space 1}   -1.58{col 46}{space 3}0.114{col 54}{space 4}-.0266005{col 67}{space 3} .0028557
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0057712{col 26}{space 2}  .001532{col 37}{space 1}   -3.77{col 46}{space 3}0.000{col 54}{space 4}-.0087787{col 67}{space 3}-.0027636
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0021777{col 26}{space 2} .0131477{col 37}{space 1}    0.17{col 46}{space 3}0.868{col 54}{space 4}-.0236338{col 67}{space 3} .0279892
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0161652{col 26}{space 2} .0480323{col 37}{space 1}   -0.34{col 46}{space 3}0.737{col 54}{space 4}-.1104621{col 67}{space 3} .0781317
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store expec_pl2
{txt}
{com}. 
. reg econ_expec i.placebo3 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       741
{txt}{hline 13}{c +}{hline 34}   F(5, 735)       = {res}     4.50
{txt}       Model {c |} {res} 9.49606787         5  1.89921357   {txt}Prob > F        ={res}    0.0005
{txt}    Residual {c |} {res} 310.312299       735  .422193604   {txt}R-squared       ={res}    0.0297
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0231
{txt}       Total {c |} {res} 319.808367       740  .432173469   {txt}Root MSE        =   {res} .64976

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo3 {c |}{col 14}{res}{space 2} .1007547{col 26}{space 2} .0542298{col 37}{space 1}    1.86{col 46}{space 3}0.064{col 54}{space 4}-.0057091{col 67}{space 3} .2072185
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0115586{col 26}{space 2} .0075503{col 37}{space 1}   -1.53{col 46}{space 3}0.126{col 54}{space 4}-.0263813{col 67}{space 3} .0032641
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0059663{col 26}{space 2} .0015387{col 37}{space 1}   -3.88{col 46}{space 3}0.000{col 54}{space 4}-.0089871{col 67}{space 3}-.0029455
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}  .000866{col 26}{space 2} .0132078{col 37}{space 1}    0.07{col 46}{space 3}0.948{col 54}{space 4}-.0250636{col 67}{space 3} .0267955
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0148044{col 26}{space 2} .0482921{col 37}{space 1}   -0.31{col 46}{space 3}0.759{col 54}{space 4}-.1096114{col 67}{space 3} .0800026
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.716774{col 26}{space 2} .1286919{col 37}{space 1}   13.34{col 46}{space 3}0.000{col 54}{space 4} 1.464126{col 67}{space 3} 1.969421
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       741
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo3 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo3 {c |}{col 14}{res}{space 2} .1007547{col 26}{space 2} .0542298{col 37}{space 1}    1.86{col 46}{space 3}0.064{col 54}{space 4}-.0057091{col 67}{space 3} .2072185
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0115586{col 26}{space 2} .0075503{col 37}{space 1}   -1.53{col 46}{space 3}0.126{col 54}{space 4}-.0263813{col 67}{space 3} .0032641
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0059663{col 26}{space 2} .0015387{col 37}{space 1}   -3.88{col 46}{space 3}0.000{col 54}{space 4}-.0089871{col 67}{space 3}-.0029455
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}  .000866{col 26}{space 2} .0132078{col 37}{space 1}    0.07{col 46}{space 3}0.948{col 54}{space 4}-.0250636{col 67}{space 3} .0267955
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0148044{col 26}{space 2} .0482921{col 37}{space 1}   -0.31{col 46}{space 3}0.759{col 54}{space 4}-.1096114{col 67}{space 3} .0800026
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store expec_pl3
{txt}
{com}. 
. reg econ_expec i.placebo4 education age occupation gender

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       741
{txt}{hline 13}{c +}{hline 34}   F(5, 735)       = {res}     5.15
{txt}       Model {c |} {res} 10.8298265         5  2.16596529   {txt}Prob > F        ={res}    0.0001
{txt}    Residual {c |} {res} 308.978541       735  .420378967   {txt}R-squared       ={res}    0.0339
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0273
{txt}       Total {c |} {res} 319.808367       740  .432173469   {txt}Root MSE        =   {res} .64837

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo4 {c |}{col 14}{res}{space 2} .1781669{col 26}{space 2} .0691446{col 37}{space 1}    2.58{col 46}{space 3}0.010{col 54}{space 4} .0424223{col 67}{space 3} .3139114
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0105702{col 26}{space 2} .0075533{col 37}{space 1}   -1.40{col 46}{space 3}0.162{col 54}{space 4}-.0253988{col 67}{space 3} .0042584
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0060584{col 26}{space 2} .0015331{col 37}{space 1}   -3.95{col 46}{space 3}0.000{col 54}{space 4}-.0090682{col 67}{space 3}-.0030486
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0005188{col 26}{space 2} .0131756{col 37}{space 1}    0.04{col 46}{space 3}0.969{col 54}{space 4}-.0253474{col 67}{space 3}  .026385
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0134439{col 26}{space 2} .0481942{col 37}{space 1}   -0.28{col 46}{space 3}0.780{col 54}{space 4}-.1080586{col 67}{space 3} .0811708
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.637986{col 26}{space 2} .1358087{col 37}{space 1}   12.06{col 46}{space 3}0.000{col 54}{space 4} 1.371367{col 67}{space 3} 1.904606
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       741
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.placebo4 education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}1.placebo4 {c |}{col 14}{res}{space 2} .1781669{col 26}{space 2} .0691446{col 37}{space 1}    2.58{col 46}{space 3}0.010{col 54}{space 4} .0424223{col 67}{space 3} .3139114
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0105702{col 26}{space 2} .0075533{col 37}{space 1}   -1.40{col 46}{space 3}0.162{col 54}{space 4}-.0253988{col 67}{space 3} .0042584
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0060584{col 26}{space 2} .0015331{col 37}{space 1}   -3.95{col 46}{space 3}0.000{col 54}{space 4}-.0090682{col 67}{space 3}-.0030486
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0005188{col 26}{space 2} .0131756{col 37}{space 1}    0.04{col 46}{space 3}0.969{col 54}{space 4}-.0253474{col 67}{space 3}  .026385
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0134439{col 26}{space 2} .0481942{col 37}{space 1}   -0.28{col 46}{space 3}0.780{col 54}{space 4}-.1080586{col 67}{space 3} .0811708
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store expec_pl4
{txt}
{com}. 
. reg econ_expec i.treated education age occupation gender if day >= 8 & day <= 14 // limited bandwith

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       451
{txt}{hline 13}{c +}{hline 34}   F(5, 445)       = {res}     3.97
{txt}       Model {c |} {res} 8.73059529         5  1.74611906   {txt}Prob > F        ={res}    0.0016
{txt}    Residual {c |} {res} 195.894682       445  .440212768   {txt}R-squared       ={res}    0.0427
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0319
{txt}       Total {c |} {res} 204.625277       450  .454722838   {txt}Root MSE        =   {res} .66349

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.2690738{col 26}{space 2} .0759555{col 37}{space 1}   -3.54{col 46}{space 3}0.000{col 54}{space 4}-.4183498{col 67}{space 3}-.1197978
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0179491{col 26}{space 2} .0109371{col 37}{space 1}   -1.64{col 46}{space 3}0.101{col 54}{space 4}-.0394439{col 67}{space 3} .0035457
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0069542{col 26}{space 2} .0021604{col 37}{space 1}   -3.22{col 46}{space 3}0.001{col 54}{space 4}-.0112001{col 67}{space 3}-.0027084
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0014156{col 26}{space 2} .0162771{col 37}{space 1}    0.09{col 46}{space 3}0.931{col 54}{space 4} -.030574{col 67}{space 3} .0334052
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0372787{col 26}{space 2} .0627945{col 37}{space 1}    0.59{col 46}{space 3}0.553{col 54}{space 4} -.086132{col 67}{space 3} .1606893
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.873195{col 26}{space 2} .1622825{col 37}{space 1}   11.54{col 46}{space 3}0.000{col 54}{space 4}  1.55426{col 67}{space 3}  2.19213
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}       451
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.treated education age occupation gender}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.2690738{col 26}{space 2} .0759555{col 37}{space 1}   -3.54{col 46}{space 3}0.000{col 54}{space 4}-.4183498{col 67}{space 3}-.1197978
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0179491{col 26}{space 2} .0109371{col 37}{space 1}   -1.64{col 46}{space 3}0.101{col 54}{space 4}-.0394439{col 67}{space 3} .0035457
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0069542{col 26}{space 2} .0021604{col 37}{space 1}   -3.22{col 46}{space 3}0.001{col 54}{space 4}-.0112001{col 67}{space 3}-.0027084
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0014156{col 26}{space 2} .0162771{col 37}{space 1}    0.09{col 46}{space 3}0.931{col 54}{space 4} -.030574{col 67}{space 3} .0334052
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0372787{col 26}{space 2} .0627945{col 37}{space 1}    0.59{col 46}{space 3}0.553{col 54}{space 4} -.086132{col 67}{space 3} .1606893
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store expec_pl5
{txt}
{com}. 
. coefplot (expec_pl*, label("Expectations")) (index_pl*, label("Index")) (evals_pl*, label("Evaluations")), ///
> keep(*.placebo* *.treated) yline(0) bycoefs vertical xlabel("") ytitle("Marginal effect") ///
> coeflabels(1.placebo = "Median Control (w/ Treated)" 1.placebo2 = "Median Control (w/o Treated)" ///
> 1.placebo3 = "6th Day" 1.placebo4 = "5th Day" 1.treated = "Reduced Bandwidth") legend(rows(1)) 
{res}{txt}
{com}. graph save FigureA6.gph, replace
{txt}(note: file FigureA6.gph not found)
{res}{txt}(file FigureA6.gph saved)

{com}. graph export FigureA6.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA6.pdf written in PDF format)

{com}. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A7 ***
.                                                                                                         ******************
. 
. ritest treated _b[treated], reps(1000) kdensityplot: logit trust_plt treated education age occupation gender if v6==13
{txt}(running logit on estimation sample)

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-572.98107}  
Iteration 1:{space 3}log likelihood = {res: -565.9842}  
Iteration 2:{space 3}log likelihood = {res:-565.95644}  
Iteration 3:{space 3}log likelihood = {res:-565.95644}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       980
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     14.05
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0153
{txt}Log likelihood = {res}-565.95644{txt}{col 49}Pseudo R2{col 67}= {res}    0.0123

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}{col 14}{res}{space 2}-.3679132{col 26}{space 2} .1826182{col 37}{space 1}   -2.01{col 46}{space 3}0.044{col 54}{space 4}-.7258383{col 67}{space 3}-.0099882
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0098183{col 26}{space 2} .0234035{col 37}{space 1}    0.42{col 46}{space 3}0.675{col 54}{space 4}-.0360517{col 67}{space 3} .0556882
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0032799{col 26}{space 2} .0045939{col 37}{space 1}   -0.71{col 46}{space 3}0.475{col 54}{space 4}-.0122838{col 67}{space 3}  .005724
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0077048{col 26}{space 2} .0378763{col 37}{space 1}    0.20{col 46}{space 3}0.839{col 54}{space 4}-.0665314{col 67}{space 3} .0819409
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.4765921{col 26}{space 2} .1459997{col 37}{space 1}   -3.26{col 46}{space 3}0.001{col 54}{space 4}-.7627463{col 67}{space 3}-.1904379
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.1077248{col 26}{space 2}   .37093{col 37}{space 1}   -0.29{col 46}{space 3}0.771{col 54}{space 4}-.8347343{col 67}{space 3} .6192846
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Resampling replications ({res}1000{txt})
{hline 4}{c +}{hline 3} 1 {hline 3}{c +}{hline 3} 2 {hline 3}{c +}{hline 3} 3 {hline 3}{c +}{hline 3} 4 {hline 3}{c +}{hline 3} 5 
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{res}{p2colset 7 17 21 2}{...}

{txt}{p2col :command:}logit trust_plt treated education age occupation gender if v6==13{p_end}
{p2colset 9 17 21 2}{...}
{p2col :_pm_1:}{res:_b[treated]}{p_end}
  res. var(s):  treated
   Resampling:  Permuting treated
Clust. var(s){res}:  __000002
     {txt}Clusters{res}:  1048
{txt}Strata var(s){res}:  none
       {txt}Strata{res}:  1

{col 1}{text}{hline 13}{c TT}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
{col 1}{text}T           {col 14}{c |}     T(obs){col 27}      c{col 35}      n{col 43}  p=c/n{col 51}  SE(p){col 59}[95% Conf. Interval]
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
{space 7}_pm_1 {c |}{col 14}{result}{space 2}-.3679132{col 27}     27{col 35}   1000{col 43} 0.0270{col 51} 0.0051{col 59} .0178669{col 69}{space 1} .0390417
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
Note: Confidence interval is with respect to p=c/n.
Note: c = #{|T| >= |T(obs)|}
{res}{txt}
{com}. gr save permutation.gph
{res}{txt}(file permutation.gph saved)

{com}. ritest treated _b[treated], reps(1000) kdensityplot: reg econ_expec treated education age occupation gender if v6==13
{txt}(running regress on estimation sample)

      Source {c |}       SS           df       MS      Number of obs   ={res}       967
{txt}{hline 13}{c +}{hline 34}   F(5, 961)       = {res}     4.69
{txt}       Model {c |} {res} 9.27590786         5  1.85518157   {txt}Prob > F        ={res}    0.0003
{txt}    Residual {c |} {res} 379.816129       961  .395230103   {txt}R-squared       ={res}    0.0238
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0188
{txt}       Total {c |} {res} 389.092037       966  .402786788   {txt}Root MSE        =   {res} .62867

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}{col 14}{res}{space 2}-.1685217{col 26}{space 2} .0501193{col 37}{space 1}   -3.36{col 46}{space 3}0.001{col 54}{space 4}-.2668775{col 67}{space 3}-.0701658
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0081534{col 26}{space 2} .0065068{col 37}{space 1}   -1.25{col 46}{space 3}0.210{col 54}{space 4}-.0209225{col 67}{space 3} .0046157
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0050616{col 26}{space 2} .0013147{col 37}{space 1}   -3.85{col 46}{space 3}0.000{col 54}{space 4}-.0076417{col 67}{space 3}-.0024815
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0040592{col 26}{space 2} .0106978{col 37}{space 1}   -0.38{col 46}{space 3}0.704{col 54}{space 4} -.025053{col 67}{space 3} .0169345
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0040894{col 26}{space 2} .0408517{col 37}{space 1}   -0.10{col 46}{space 3}0.920{col 54}{space 4}-.0842583{col 67}{space 3} .0760795
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.741159{col 26}{space 2} .1057096{col 37}{space 1}   16.47{col 46}{space 3}0.000{col 54}{space 4}  1.53371{col 67}{space 3} 1.948607
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Resampling replications ({res}1000{txt})
{hline 4}{c +}{hline 3} 1 {hline 3}{c +}{hline 3} 2 {hline 3}{c +}{hline 3} 3 {hline 3}{c +}{hline 3} 4 {hline 3}{c +}{hline 3} 5 
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{res}{p2colset 7 17 21 2}{...}

{txt}{p2col :command:}regress econ_expec treated education age occupation gender if v6==13{p_end}
{p2colset 9 17 21 2}{...}
{p2col :_pm_1:}{res:_b[treated]}{p_end}
  res. var(s):  treated
   Resampling:  Permuting treated
Clust. var(s){res}:  __000002
     {txt}Clusters{res}:  1048
{txt}Strata var(s){res}:  none
       {txt}Strata{res}:  1

{col 1}{text}{hline 13}{c TT}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
{col 1}{text}T           {col 14}{c |}     T(obs){col 27}      c{col 35}      n{col 43}  p=c/n{col 51}  SE(p){col 59}[95% Conf. Interval]
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
{space 7}_pm_1 {c |}{col 14}{result}{space 2}-.1685217{col 27}      0{col 35}   1000{col 43} 0.0000{col 51} 0.0000{col 59}        0{col 69}{space 1} .0036821
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
Note: Confidence interval is with respect to p=c/n.
Note: c = #{|T| >= |T(obs)|}
{res}{txt}
{com}. gr save permutation2.gph
{res}{txt}(file permutation2.gph saved)

{com}. ritest treated _b[treated], reps(1000) kdensityplot: reg econ_evals  treated education age occupation gender if v6==13
{txt}(running regress on estimation sample)

      Source {c |}       SS           df       MS      Number of obs   ={res}     1,022
{txt}{hline 13}{c +}{hline 34}   F(5, 1016)      = {res}     1.54
{txt}       Model {c |} {res} 2.59101122         5  .518202243   {txt}Prob > F        ={res}    0.1753
{txt}    Residual {c |} {res} 342.391376     1,016  .336999386   {txt}R-squared       ={res}    0.0075
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0026
{txt}       Total {c |} {res} 344.982387     1,021  .337886765   {txt}Root MSE        =   {res} .58052

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}{col 14}{res}{space 2}-.1043934{col 26}{space 2} .0451675{col 37}{space 1}   -2.31{col 46}{space 3}0.021{col 54}{space 4}-.1930257{col 67}{space 3}-.0157611
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0007231{col 26}{space 2} .0058071{col 37}{space 1}   -0.12{col 46}{space 3}0.901{col 54}{space 4}-.0121184{col 67}{space 3} .0106723
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0005282{col 26}{space 2} .0011572{col 37}{space 1}   -0.46{col 46}{space 3}0.648{col 54}{space 4} -.002799{col 67}{space 3} .0017426
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0051852{col 26}{space 2} .0095993{col 37}{space 1}   -0.54{col 46}{space 3}0.589{col 54}{space 4}-.0240219{col 67}{space 3} .0136514
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0596216{col 26}{space 2}  .036727{col 37}{space 1}   -1.62{col 46}{space 3}0.105{col 54}{space 4}-.1316911{col 67}{space 3} .0124479
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.692779{col 26}{space 2} .0942653{col 37}{space 1}   17.96{col 46}{space 3}0.000{col 54}{space 4} 1.507803{col 67}{space 3} 1.877756
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Resampling replications ({res}1000{txt})
{hline 4}{c +}{hline 3} 1 {hline 3}{c +}{hline 3} 2 {hline 3}{c +}{hline 3} 3 {hline 3}{c +}{hline 3} 4 {hline 3}{c +}{hline 3} 5 
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{res}{p2colset 7 17 21 2}{...}

{txt}{p2col :command:}regress econ_evals treated education age occupation gender if v6==13{p_end}
{p2colset 9 17 21 2}{...}
{p2col :_pm_1:}{res:_b[treated]}{p_end}
  res. var(s):  treated
   Resampling:  Permuting treated
Clust. var(s){res}:  __000002
     {txt}Clusters{res}:  1048
{txt}Strata var(s){res}:  none
       {txt}Strata{res}:  1

{col 1}{text}{hline 13}{c TT}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
{col 1}{text}T           {col 14}{c |}     T(obs){col 27}      c{col 35}      n{col 43}  p=c/n{col 51}  SE(p){col 59}[95% Conf. Interval]
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
{space 7}_pm_1 {c |}{col 14}{result}{space 2}-.1043934{col 27}     18{col 35}   1000{col 43} 0.0180{col 51} 0.0042{col 59} .0107019{col 69}{space 1}  .028299
{col 1}{text}{hline 13}{c BT}{hline 12}{hline 8}{hline 8}{hline 8}{hline 8}{hline 10}{hline 10}
Note: Confidence interval is with respect to p=c/n.
Note: c = #{|T| >= |T(obs)|}
{res}{txt}
{com}. gr save permutation3.gph
{res}{txt}(file permutation3.gph saved)

{com}. 
. gr combine permutation.gph permutation2.gph permutation3.gph
{res}{txt}
{com}. graph save FigureA7.gph, replace
{txt}(note: file FigureA7.gph not found)
{res}{txt}(file FigureA7.gph saved)

{com}. graph export FigureA7.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA7.pdf written in PDF format)

{com}. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A8 ***
.                                                                                                         ******************
. ** Reload the data as previous version dropped portugal
.                                                                                                         
. use "/Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/eb75.3_2011.dta", clear
{txt}
{com}. 
. ** Rerun necessary data cleaning
. 
. drop if v6 == 33 | v6 == 31 | v6 == 35 | v6 == 43 | v6 == 34 // drop non-EU countries.
{txt}(4,056 observations deleted)

{com}. replace v6 = 4 if v6 == 14 // merge East/West DE
{txt}(523 real changes made)

{com}. replace v6 = 9 if v6 == 10 // merge GB/NI
{txt}(300 real changes made)

{com}. 
. gen treated = 1 if v651 > 11 // keep if interviewed after intervention date (i.e treated)
{txt}(18,825 missing values generated)

{com}. replace treated = 0 if v651 < 12
{txt}(18,825 real changes made)

{com}. tab treated

    {txt}treated {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}     18,825       67.93       67.93
{txt}          1 {c |}{res}      8,888       32.07      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     27,713      100.00
{txt}
{com}. 
. recode v311 (2=0) (1=1), generate (trust_plt) // trust parliament
{txt}(16520 differences between v311 and trust_plt)

{com}. 
. recode v140 (1=4) (2=3) (3=2) (4=1), gen(econ_index) /* variable summarises answers to v127/140. As from the documentation:
>                                                 Respondents coded 1 or 2 in V114 or V120 and coded 1 in V127 or V134 are coded 1 ("Satisfied and confident") in the index variable. 
>                                                 Respondents coded 3 or 4 in V114 or V120 and coded 1 in V127 or V134 are coded 2 ("Unsatisfied and confident") in the index variable. 
>                                                 Respondents coded 1 or 2 in V114 or V120 and coded 2 in V127 or V134 are coded 3 ("Satisfied and worried") in the index variable. 
>                                                 Respondents coded 3 or 4 in V114 or V120 and coded 2 in V127 or V134 are coded 4 ("Unsatisfied and worried") in the index variable. 
>                                                 Respondents coded 5 in V114 or V120 or coded 3 or 4 in V127 or V134 are coded 5 ("INAP") in the index variable. */
{txt}(14714 differences between v140 and econ_index)

{com}. 
. recode v127 (1=3) (2=1) (3=2), gen(econ_expec) /* What are your expectations for the next twelve months: will the next twelve months be better, worse or the same, when it comes to...?
>                                                                                                 The economic situation in [Our Country]. 1 = better, 2 = worse, 3 = same, 4 = DK */
{txt}(26596 differences between v127 and econ_expec)

{com}. 
. recode v114 (1=4) (2=3) (3=2) (4=1), gen(econ_evals) /* How would you judge the current situation in each of the following?
>                                                 The situation of the [nationality] economy? 1= VG 2= Rather G 3= RB 4= VB 5 = DK */
{txt}(27351 differences between v114 and econ_evals)

{com}. 
. 
. rename v616 age
{res}{txt}
{com}. rename v614 education
{res}{txt}
{com}. rename v752 occupation
{res}{txt}
{com}. rename v615 gender
{res}{txt}
{com}. 
. label variable treated "Treatment"
{txt}
{com}. label define treated 0 "Control" 1 "Treated"
{txt}
{com}. label values treated treated
{txt}
{com}. 
. label variable age "Age (years)"
{txt}
{com}. label variable education "Education"
{txt}
{com}. label variable occupation "Occupation"
{txt}
{com}. 
. 
. 
.   levelsof v6, local(levs)
{res}{txt}1 2 3 4 5 6 7 8 9 11 12 13 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 32

{com}.  foreach n in `levs' {c -(}
{txt}  2{com}. display ""
{txt}  3{com}. display "======== Regression for level: `n' ========="
{txt}  4{com}. logit trust_plt i.treated education age occupation gender if v6 == `n'
{txt}  5{com}. estimates store cntry_plac_`n'
{txt}  6{com}.  {c )-}

======== Regression for level: 1 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-605.73863}  
Iteration 1:{space 3}log likelihood = {res:-578.31277}  
Iteration 2:{space 3}log likelihood = {res:-578.16078}  
Iteration 3:{space 3}log likelihood = {res:-578.16075}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       932
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     55.16
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-578.16075{txt}{col 49}Pseudo R2{col 67}= {res}    0.0455

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .1115819{col 26}{space 2} .1650215{col 37}{space 1}    0.68{col 46}{space 3}0.499{col 54}{space 4}-.2118544{col 67}{space 3} .4350182
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1323426{col 26}{space 2} .0281852{col 37}{space 1}    4.70{col 46}{space 3}0.000{col 54}{space 4} .0771007{col 67}{space 3} .1875846
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0286916{col 26}{space 2} .0046128{col 37}{space 1}    6.22{col 46}{space 3}0.000{col 54}{space 4} .0196506{col 67}{space 3} .0377325
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0454871{col 26}{space 2} .0374235{col 37}{space 1}    1.22{col 46}{space 3}0.224{col 54}{space 4}-.0278617{col 67}{space 3} .1188359
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0735896{col 26}{space 2} .1421551{col 37}{space 1}    0.52{col 46}{space 3}0.605{col 54}{space 4}-.2050293{col 67}{space 3} .3522084
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.196865{col 26}{space 2} .4389392{col 37}{space 1}   -7.28{col 46}{space 3}0.000{col 54}{space 4} -4.05717{col 67}{space 3} -2.33656
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 2 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res: -690.7197}  
Iteration 1:{space 3}log likelihood = {res: -670.9736}  
Iteration 2:{space 3}log likelihood = {res:-670.94727}  
Iteration 3:{space 3}log likelihood = {res:-670.94727}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,001
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     39.54
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-670.94727{txt}{col 49}Pseudo R2{col 67}= {res}    0.0286

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .3020385{col 26}{space 2} .1295202{col 37}{space 1}    2.33{col 46}{space 3}0.020{col 54}{space 4} .0481835{col 67}{space 3} .5558935
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1203812{col 26}{space 2} .0270977{col 37}{space 1}    4.44{col 46}{space 3}0.000{col 54}{space 4} .0672708{col 67}{space 3} .1734917
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0165945{col 26}{space 2} .0043794{col 37}{space 1}    3.79{col 46}{space 3}0.000{col 54}{space 4} .0080109{col 67}{space 3} .0251781
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0217108{col 26}{space 2}  .033291{col 37}{space 1}   -0.65{col 46}{space 3}0.514{col 54}{space 4}-.0869599{col 67}{space 3} .0435383
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.3823509{col 26}{space 2} .1295979{col 37}{space 1}   -2.95{col 46}{space 3}0.003{col 54}{space 4}-.6363581{col 67}{space 3}-.1283437
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.164379{col 26}{space 2} .4140314{col 37}{space 1}   -2.81{col 46}{space 3}0.005{col 54}{space 4}-1.975866{col 67}{space 3}-.3528927
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 3 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-628.58876}  
Iteration 1:{space 3}log likelihood = {res:-608.09636}  
Iteration 2:{space 3}log likelihood = {res:-607.99577}  
Iteration 3:{space 3}log likelihood = {res:-607.99576}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       975
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     41.19
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-607.99576{txt}{col 49}Pseudo R2{col 67}= {res}    0.0328

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.0087924{col 26}{space 2}  .141188{col 37}{space 1}   -0.06{col 46}{space 3}0.950{col 54}{space 4}-.2855158{col 67}{space 3}  .267931
{txt}{space 3}education {c |}{col 14}{res}{space 2}  .163008{col 26}{space 2} .0286511{col 37}{space 1}    5.69{col 46}{space 3}0.000{col 54}{space 4}  .106853{col 67}{space 3} .2191631
{txt}{space 9}age {c |}{col 14}{res}{space 2}   .01332{col 26}{space 2} .0044447{col 37}{space 1}    3.00{col 46}{space 3}0.003{col 54}{space 4} .0046084{col 67}{space 3} .0220315
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0263508{col 26}{space 2} .0315071{col 37}{space 1}   -0.84{col 46}{space 3}0.403{col 54}{space 4}-.0881036{col 67}{space 3} .0354019
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.2950186{col 26}{space 2} .1393806{col 37}{space 1}   -2.12{col 46}{space 3}0.034{col 54}{space 4}-.5681994{col 67}{space 3}-.0218377
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.5615708{col 26}{space 2} .4432408{col 37}{space 1}   -1.27{col 46}{space 3}0.205{col 54}{space 4}-1.430307{col 67}{space 3} .3071653
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 4 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-995.07489}  
Iteration 1:{space 3}log likelihood = {res: -973.6111}  
Iteration 2:{space 3}log likelihood = {res:-973.59791}  
Iteration 3:{space 3}log likelihood = {res:-973.59791}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,437
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     42.95
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-973.59791{txt}{col 49}Pseudo R2{col 67}= {res}    0.0216

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .0333817{col 26}{space 2} .1073768{col 37}{space 1}    0.31{col 46}{space 3}0.756{col 54}{space 4} -.177073{col 67}{space 3} .2438364
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1217444{col 26}{space 2} .0198178{col 37}{space 1}    6.14{col 46}{space 3}0.000{col 54}{space 4} .0829024{col 67}{space 3} .1605865
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0142174{col 26}{space 2} .0032712{col 37}{space 1}    4.35{col 46}{space 3}0.000{col 54}{space 4} .0078059{col 67}{space 3} .0206289
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} -.013348{col 26}{space 2} .0256453{col 37}{space 1}   -0.52{col 46}{space 3}0.603{col 54}{space 4} -.063612{col 67}{space 3} .0369159
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0633542{col 26}{space 2} .1083639{col 37}{space 1}    0.58{col 46}{space 3}0.559{col 54}{space 4}-.1490352{col 67}{space 3} .2757436
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.456368{col 26}{space 2} .3120882{col 37}{space 1}   -4.67{col 46}{space 3}0.000{col 54}{space 4}-2.068049{col 67}{space 3} -.844686
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 5 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-549.48294}  
Iteration 1:{space 3}log likelihood = {res:-534.21237}  
Iteration 2:{space 3}log likelihood = {res:-533.97695}  
Iteration 3:{space 3}log likelihood = {res:-533.97576}  
Iteration 4:{space 3}log likelihood = {res:-533.97576}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       904
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     31.01
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-533.97576{txt}{col 49}Pseudo R2{col 67}= {res}    0.0282

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}  -1.1651{col 26}{space 2} .6275035{col 37}{space 1}   -1.86{col 46}{space 3}0.063{col 54}{space 4}-2.394984{col 67}{space 3}  .064784
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1153753{col 26}{space 2} .0277809{col 37}{space 1}    4.15{col 46}{space 3}0.000{col 54}{space 4} .0609257{col 67}{space 3} .1698249
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0014426{col 26}{space 2} .0052014{col 37}{space 1}    0.28{col 46}{space 3}0.782{col 54}{space 4}-.0087519{col 67}{space 3} .0116372
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0839797{col 26}{space 2} .0341792{col 37}{space 1}   -2.46{col 46}{space 3}0.014{col 54}{space 4}-.1509697{col 67}{space 3}-.0169896
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0980022{col 26}{space 2}  .151469{col 37}{space 1}    0.65{col 46}{space 3}0.518{col 54}{space 4}-.1988716{col 67}{space 3}  .394876
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.297822{col 26}{space 2} .4088469{col 37}{space 1}   -3.17{col 46}{space 3}0.002{col 54}{space 4}-2.099147{col 67}{space 3} -.496497
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 6 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-239.28963}  
Iteration 1:{space 3}log likelihood = {res: -234.1584}  
Iteration 2:{space 3}log likelihood = {res:-234.11129}  
Iteration 3:{space 3}log likelihood = {res:-234.11128}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       427
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     10.36
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0657
{txt}Log likelihood = {res}-234.11128{txt}{col 49}Pseudo R2{col 67}= {res}    0.0216

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.1109636{col 26}{space 2} .3226873{col 37}{space 1}   -0.34{col 46}{space 3}0.731{col 54}{space 4} -.743419{col 67}{space 3} .5214919
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1196635{col 26}{space 2} .0419866{col 37}{space 1}    2.85{col 46}{space 3}0.004{col 54}{space 4} .0373714{col 67}{space 3} .2019557
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0168164{col 26}{space 2} .0079922{col 37}{space 1}    2.10{col 46}{space 3}0.035{col 54}{space 4} .0011519{col 67}{space 3} .0324809
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0048239{col 26}{space 2} .0584342{col 37}{space 1}    0.08{col 46}{space 3}0.934{col 54}{space 4} -.109705{col 67}{space 3} .1193527
{txt}{space 6}gender {c |}{col 14}{res}{space 2}   .22322{col 26}{space 2} .2319407{col 37}{space 1}    0.96{col 46}{space 3}0.336{col 54}{space 4}-.2313755{col 67}{space 3} .6778155
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.8290675{col 26}{space 2} .7270405{col 37}{space 1}   -1.14{col 46}{space 3}0.254{col 54}{space 4}-2.254041{col 67}{space 3} .5959057
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 7 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-613.12003}  
Iteration 1:{space 3}log likelihood = {res:-604.05622}  
Iteration 2:{space 3}log likelihood = {res:-604.02576}  
Iteration 3:{space 3}log likelihood = {res:-604.02576}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       980
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     18.19
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0027
{txt}Log likelihood = {res}-604.02576{txt}{col 49}Pseudo R2{col 67}= {res}    0.0148

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .1251403{col 26}{space 2} .1468005{col 37}{space 1}    0.85{col 46}{space 3}0.394{col 54}{space 4}-.1625834{col 67}{space 3}  .412864
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0777767{col 26}{space 2} .0287919{col 37}{space 1}    2.70{col 46}{space 3}0.007{col 54}{space 4} .0213455{col 67}{space 3} .1342078
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0052816{col 26}{space 2}  .004028{col 37}{space 1}    1.31{col 46}{space 3}0.190{col 54}{space 4}-.0026131{col 67}{space 3} .0131764
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0893305{col 26}{space 2} .0320988{col 37}{space 1}   -2.78{col 46}{space 3}0.005{col 54}{space 4}-.1522429{col 67}{space 3}-.0264181
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.1034892{col 26}{space 2} .1387527{col 37}{space 1}   -0.75{col 46}{space 3}0.456{col 54}{space 4}-.3754395{col 67}{space 3}  .168461
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4529865{col 26}{space 2} .4294356{col 37}{space 1}    1.05{col 46}{space 3}0.291{col 54}{space 4}-.3886918{col 67}{space 3} 1.294665
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 8 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-613.32516}  
Iteration 1:{space 3}log likelihood = {res:-588.47406}  
Iteration 2:{space 3}log likelihood = {res:-588.40951}  
Iteration 3:{space 3}log likelihood = {res: -588.4095}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       892
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     49.83
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -588.4095{txt}{col 49}Pseudo R2{col 67}= {res}    0.0406

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .3129704{col 26}{space 2} .1406874{col 37}{space 1}    2.22{col 46}{space 3}0.026{col 54}{space 4} .0372281{col 67}{space 3} .5887127
{txt}{space 3}education {c |}{col 14}{res}{space 2}  .165515{col 26}{space 2} .0298494{col 37}{space 1}    5.54{col 46}{space 3}0.000{col 54}{space 4} .1070111{col 67}{space 3} .2240188
{txt}{space 9}age {c |}{col 14}{res}{space 2}  .022542{col 26}{space 2} .0047114{col 37}{space 1}    4.78{col 46}{space 3}0.000{col 54}{space 4} .0133078{col 67}{space 3} .0317762
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0575755{col 26}{space 2}  .035962{col 37}{space 1}    1.60{col 46}{space 3}0.109{col 54}{space 4}-.0129088{col 67}{space 3} .1280598
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.2773267{col 26}{space 2}  .139363{col 37}{space 1}   -1.99{col 46}{space 3}0.047{col 54}{space 4}-.5504732{col 67}{space 3}-.0041803
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.095942{col 26}{space 2}  .428725{col 37}{space 1}   -4.89{col 46}{space 3}0.000{col 54}{space 4}-2.936228{col 67}{space 3}-1.255657
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 9 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-743.08239}  
Iteration 1:{space 3}log likelihood = {res:-718.22981}  
Iteration 2:{space 3}log likelihood = {res:-718.08766}  
Iteration 3:{space 3}log likelihood = {res:-718.08765}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}     1,190
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     49.99
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-718.08765{txt}{col 49}Pseudo R2{col 67}= {res}    0.0336

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .1587345{col 26}{space 2} .1299499{col 37}{space 1}    1.22{col 46}{space 3}0.222{col 54}{space 4}-.0959626{col 67}{space 3} .4134315
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1613792{col 26}{space 2} .0248104{col 37}{space 1}    6.50{col 46}{space 3}0.000{col 54}{space 4} .1127517{col 67}{space 3} .2100068
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0142304{col 26}{space 2} .0038605{col 37}{space 1}    3.69{col 46}{space 3}0.000{col 54}{space 4} .0066639{col 67}{space 3} .0217969
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0279065{col 26}{space 2} .0298709{col 37}{space 1}    0.93{col 46}{space 3}0.350{col 54}{space 4}-.0306393{col 67}{space 3} .0864523
{txt}{space 6}gender {c |}{col 14}{res}{space 2} -.160139{col 26}{space 2} .1282516{col 37}{space 1}   -1.25{col 46}{space 3}0.212{col 54}{space 4}-.4115074{col 67}{space 3} .0912295
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.247098{col 26}{space 2} .3660412{col 37}{space 1}   -6.14{col 46}{space 3}0.000{col 54}{space 4}-2.964526{col 67}{space 3} -1.52967
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 11 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-460.82906}  
Iteration 1:{space 3}log likelihood = {res:-457.31541}  
Iteration 2:{space 3}log likelihood = {res:-457.28652}  
Iteration 3:{space 3}log likelihood = {res:-457.28652}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       993
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}      7.09
{txt}{col 49}Prob > chi2{col 67}= {res}    0.2144
{txt}Log likelihood = {res}-457.28652{txt}{col 49}Pseudo R2{col 67}= {res}    0.0077

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .3555305{col 26}{space 2} .2658492{col 37}{space 1}    1.34{col 46}{space 3}0.181{col 54}{space 4}-.1655244{col 67}{space 3} .8765854
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0277313{col 26}{space 2} .0307523{col 37}{space 1}    0.90{col 46}{space 3}0.367{col 54}{space 4}-.0325421{col 67}{space 3} .0880046
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0069749{col 26}{space 2} .0056684{col 37}{space 1}    1.23{col 46}{space 3}0.219{col 54}{space 4} -.004135{col 67}{space 3} .0180848
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0078563{col 26}{space 2} .0367939{col 37}{space 1}    0.21{col 46}{space 3}0.831{col 54}{space 4}-.0642584{col 67}{space 3}  .079971
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.3103388{col 26}{space 2} .1696361{col 37}{space 1}   -1.83{col 46}{space 3}0.067{col 54}{space 4}-.6428194{col 67}{space 3} .0221418
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} -1.62395{col 26}{space 2} .4517741{col 37}{space 1}   -3.59{col 46}{space 3}0.000{col 54}{space 4}-2.509411{col 67}{space 3}-.7384892
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 12 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-494.63593}  
Iteration 1:{space 3}log likelihood = {res:-490.77901}  
Iteration 2:{space 3}log likelihood = {res:-490.76411}  
Iteration 3:{space 3}log likelihood = {res:-490.76411}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       908
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}      7.74
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1709
{txt}Log likelihood = {res}-490.76411{txt}{col 49}Pseudo R2{col 67}= {res}    0.0078

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.0053101{col 26}{space 2} .1658309{col 37}{space 1}   -0.03{col 46}{space 3}0.974{col 54}{space 4}-.3303326{col 67}{space 3} .3197125
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0287495{col 26}{space 2} .0244421{col 37}{space 1}    1.18{col 46}{space 3}0.240{col 54}{space 4}-.0191561{col 67}{space 3} .0766551
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0113851{col 26}{space 2} .0048229{col 37}{space 1}    2.36{col 46}{space 3}0.018{col 54}{space 4} .0019324{col 67}{space 3} .0208378
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0441703{col 26}{space 2} .0414622{col 37}{space 1}   -1.07{col 46}{space 3}0.287{col 54}{space 4}-.1254347{col 67}{space 3} .0370941
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.2263662{col 26}{space 2} .1585983{col 37}{space 1}   -1.43{col 46}{space 3}0.153{col 54}{space 4}-.5372132{col 67}{space 3} .0844807
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.295858{col 26}{space 2} .4149664{col 37}{space 1}   -3.12{col 46}{space 3}0.002{col 54}{space 4}-2.109178{col 67}{space 3}-.4825392
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 13 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-572.98107}  
Iteration 1:{space 3}log likelihood = {res: -565.9842}  
Iteration 2:{space 3}log likelihood = {res:-565.95644}  
Iteration 3:{space 3}log likelihood = {res:-565.95644}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       980
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     14.05
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0153
{txt}Log likelihood = {res}-565.95644{txt}{col 49}Pseudo R2{col 67}= {res}    0.0123

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.3679132{col 26}{space 2} .1826182{col 37}{space 1}   -2.01{col 46}{space 3}0.044{col 54}{space 4}-.7258383{col 67}{space 3}-.0099882
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0098183{col 26}{space 2} .0234035{col 37}{space 1}    0.42{col 46}{space 3}0.675{col 54}{space 4}-.0360517{col 67}{space 3} .0556882
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0032799{col 26}{space 2} .0045939{col 37}{space 1}   -0.71{col 46}{space 3}0.475{col 54}{space 4}-.0122838{col 67}{space 3}  .005724
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0077048{col 26}{space 2} .0378763{col 37}{space 1}    0.20{col 46}{space 3}0.839{col 54}{space 4}-.0665314{col 67}{space 3} .0819409
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.4765921{col 26}{space 2} .1459997{col 37}{space 1}   -3.26{col 46}{space 3}0.001{col 54}{space 4}-.7627463{col 67}{space 3}-.1904379
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.1077248{col 26}{space 2}   .37093{col 37}{space 1}   -0.29{col 46}{space 3}0.771{col 54}{space 4}-.8347343{col 67}{space 3} .6192846
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 16 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-591.45525}  
Iteration 1:{space 3}log likelihood = {res:-567.40354}  
Iteration 2:{space 3}log likelihood = {res:-567.21756}  
Iteration 3:{space 3}log likelihood = {res:-567.21752}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       934
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     48.48
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-567.21752{txt}{col 49}Pseudo R2{col 67}= {res}    0.0410

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .1040357{col 26}{space 2} .1458875{col 37}{space 1}    0.71{col 46}{space 3}0.476{col 54}{space 4}-.1818986{col 67}{space 3}   .38997
{txt}{space 3}education {c |}{col 14}{res}{space 2}  .146928{col 26}{space 2} .0275876{col 37}{space 1}    5.33{col 46}{space 3}0.000{col 54}{space 4} .0928572{col 67}{space 3} .2009988
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0097445{col 26}{space 2} .0045913{col 37}{space 1}    2.12{col 46}{space 3}0.034{col 54}{space 4} .0007457{col 67}{space 3} .0187434
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} -.026547{col 26}{space 2} .0330393{col 37}{space 1}   -0.80{col 46}{space 3}0.422{col 54}{space 4}-.0913029{col 67}{space 3} .0382089
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.6138762{col 26}{space 2} .1458071{col 37}{space 1}   -4.21{col 46}{space 3}0.000{col 54}{space 4}-.8996528{col 67}{space 3}-.3280996
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2837181{col 26}{space 2} .4435329{col 37}{space 1}    0.64{col 46}{space 3}0.522{col 54}{space 4}-.5855904{col 67}{space 3} 1.153027
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 17 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-536.24028}  
Iteration 1:{space 3}log likelihood = {res:-526.69201}  
Iteration 2:{space 3}log likelihood = {res:-526.61467}  
Iteration 3:{space 3}log likelihood = {res:-526.61466}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       984
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     19.25
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0017
{txt}Log likelihood = {res}-526.61466{txt}{col 49}Pseudo R2{col 67}= {res}    0.0180

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .0959943{col 26}{space 2} .1611614{col 37}{space 1}    0.60{col 46}{space 3}0.551{col 54}{space 4}-.2198762{col 67}{space 3} .4118648
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0935243{col 26}{space 2} .0293072{col 37}{space 1}    3.19{col 46}{space 3}0.001{col 54}{space 4} .0360833{col 67}{space 3} .1509653
{txt}{space 9}age {c |}{col 14}{res}{space 2}  .011522{col 26}{space 2} .0051254{col 37}{space 1}    2.25{col 46}{space 3}0.025{col 54}{space 4} .0014765{col 67}{space 3} .0215675
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0563862{col 26}{space 2} .0364978{col 37}{space 1}   -1.54{col 46}{space 3}0.122{col 54}{space 4}-.1279207{col 67}{space 3} .0151483
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.4102144{col 26}{space 2} .1555441{col 37}{space 1}   -2.64{col 46}{space 3}0.008{col 54}{space 4}-.7150752{col 67}{space 3}-.1053536
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7530373{col 26}{space 2} .4532999{col 37}{space 1}    1.66{col 46}{space 3}0.097{col 54}{space 4}-.1354142{col 67}{space 3} 1.641489
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 18 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-591.20105}  
Iteration 1:{space 3}log likelihood = {res:-585.98288}  
Iteration 2:{space 3}log likelihood = {res:-585.97152}  
Iteration 3:{space 3}log likelihood = {res:-585.97152}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       937
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     10.46
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0632
{txt}Log likelihood = {res}-585.97152{txt}{col 49}Pseudo R2{col 67}= {res}    0.0088

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .3714165{col 26}{space 2} .1531636{col 37}{space 1}    2.42{col 46}{space 3}0.015{col 54}{space 4} .0712215{col 67}{space 3} .6716116
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0501048{col 26}{space 2} .0300292{col 37}{space 1}    1.67{col 46}{space 3}0.095{col 54}{space 4}-.0087513{col 67}{space 3} .1089609
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0025122{col 26}{space 2} .0048564{col 37}{space 1}   -0.52{col 46}{space 3}0.605{col 54}{space 4}-.0120305{col 67}{space 3} .0070061
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0135918{col 26}{space 2} .0377483{col 37}{space 1}   -0.36{col 46}{space 3}0.719{col 54}{space 4} -.087577{col 67}{space 3} .0603935
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.0683897{col 26}{space 2} .1428402{col 37}{space 1}   -0.48{col 46}{space 3}0.632{col 54}{space 4}-.3483512{col 67}{space 3} .2115719
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6691478{col 26}{space 2} .3843316{col 37}{space 1}    1.74{col 46}{space 3}0.082{col 54}{space 4}-.0841283{col 67}{space 3} 1.422424
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 19 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-325.57898}  
Iteration 1:{space 3}log likelihood = {res:-314.80441}  
Iteration 2:{space 3}log likelihood = {res:-314.79186}  
Iteration 3:{space 3}log likelihood = {res:-314.79186}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       471
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     21.57
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0006
{txt}Log likelihood = {res}-314.79186{txt}{col 49}Pseudo R2{col 67}= {res}    0.0331

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .4343524{col 26}{space 2} .2245056{col 37}{space 1}    1.93{col 46}{space 3}0.053{col 54}{space 4}-.0056704{col 67}{space 3} .8743753
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0502662{col 26}{space 2} .0382161{col 37}{space 1}   -1.32{col 46}{space 3}0.188{col 54}{space 4}-.1251683{col 67}{space 3} .0246359
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0150953{col 26}{space 2} .0068825{col 37}{space 1}    2.19{col 46}{space 3}0.028{col 54}{space 4} .0016058{col 67}{space 3} .0285847
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0618139{col 26}{space 2}  .045129{col 37}{space 1}    1.37{col 46}{space 3}0.171{col 54}{space 4}-.0266373{col 67}{space 3} .1502651
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.1190712{col 26}{space 2}  .189318{col 37}{space 1}   -0.63{col 46}{space 3}0.529{col 54}{space 4}-.4901278{col 67}{space 3} .2519853
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.7745273{col 26}{space 2} .5985096{col 37}{space 1}   -1.29{col 46}{space 3}0.196{col 54}{space 4}-1.947584{col 67}{space 3} .3985299
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 20 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-356.76351}  
Iteration 1:{space 3}log likelihood = {res:-351.50451}  
Iteration 2:{space 3}log likelihood = {res:-351.40906}  
Iteration 3:{space 3}log likelihood = {res:-351.40902}  
Iteration 4:{space 3}log likelihood = {res:-351.40902}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       983
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     10.71
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0575
{txt}Log likelihood = {res}-351.40902{txt}{col 49}Pseudo R2{col 67}= {res}    0.0150

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.4353397{col 26}{space 2} .2618879{col 37}{space 1}   -1.66{col 46}{space 3}0.096{col 54}{space 4}-.9486304{col 67}{space 3} .0779511
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1324235{col 26}{space 2} .0539796{col 37}{space 1}    2.45{col 46}{space 3}0.014{col 54}{space 4} .0266254{col 67}{space 3} .2382217
{txt}{space 9}age {c |}{col 14}{res}{space 2}  .000711{col 26}{space 2} .0066001{col 37}{space 1}    0.11{col 46}{space 3}0.914{col 54}{space 4}-.0122249{col 67}{space 3} .0136469
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0453423{col 26}{space 2} .0457593{col 37}{space 1}   -0.99{col 46}{space 3}0.322{col 54}{space 4}-.1350288{col 67}{space 3} .0443442
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .1730387{col 26}{space 2} .2038276{col 37}{space 1}    0.85{col 46}{space 3}0.396{col 54}{space 4}-.2264561{col 67}{space 3} .5725335
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.817344{col 26}{space 2} .6128985{col 37}{space 1}   -4.60{col 46}{space 3}0.000{col 54}{space 4}-4.018603{col 67}{space 3}-1.616085
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 21 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-644.36664}  
Iteration 1:{space 3}log likelihood = {res: -634.8178}  
Iteration 2:{space 3}log likelihood = {res:-634.81456}  
Iteration 3:{space 3}log likelihood = {res:-634.81456}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       930
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     19.10
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0018
{txt}Log likelihood = {res}-634.81456{txt}{col 49}Pseudo R2{col 67}= {res}    0.0148

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .0692799{col 26}{space 2} .1341882{col 37}{space 1}    0.52{col 46}{space 3}0.606{col 54}{space 4}-.1937243{col 67}{space 3}  .332284
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0915694{col 26}{space 2} .0295295{col 37}{space 1}    3.10{col 46}{space 3}0.002{col 54}{space 4} .0336925{col 67}{space 3} .1494462
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0000254{col 26}{space 2} .0039249{col 37}{space 1}   -0.01{col 46}{space 3}0.995{col 54}{space 4}-.0077181{col 67}{space 3} .0076672
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} -.071194{col 26}{space 2} .0300747{col 37}{space 1}   -2.37{col 46}{space 3}0.018{col 54}{space 4}-.1301393{col 67}{space 3}-.0122488
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.1094083{col 26}{space 2} .1360964{col 37}{space 1}   -0.80{col 46}{space 3}0.421{col 54}{space 4}-.3761523{col 67}{space 3} .1573358
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.1403252{col 26}{space 2} .3988577{col 37}{space 1}   -0.35{col 46}{space 3}0.725{col 54}{space 4}-.9220719{col 67}{space 3} .6414214
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 22 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-641.80044}  
Iteration 1:{space 3}log likelihood = {res:-640.03666}  
Iteration 2:{space 3}log likelihood = {res:-640.03605}  
Iteration 3:{space 3}log likelihood = {res:-640.03605}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       971
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}      3.53
{txt}{col 49}Prob > chi2{col 67}= {res}    0.6190
{txt}Log likelihood = {res}-640.03605{txt}{col 49}Pseudo R2{col 67}= {res}    0.0027

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .2306059{col 26}{space 2} .1588961{col 37}{space 1}    1.45{col 46}{space 3}0.147{col 54}{space 4}-.0808247{col 67}{space 3} .5420365
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0210555{col 26}{space 2} .0273687{col 37}{space 1}    0.77{col 46}{space 3}0.442{col 54}{space 4}-.0325862{col 67}{space 3} .0746972
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0043695{col 26}{space 2} .0044218{col 37}{space 1}    0.99{col 46}{space 3}0.323{col 54}{space 4} -.004297{col 67}{space 3} .0130361
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0109033{col 26}{space 2} .0387993{col 37}{space 1}   -0.28{col 46}{space 3}0.779{col 54}{space 4}-.0869485{col 67}{space 3} .0651419
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .0354224{col 26}{space 2} .1364683{col 37}{space 1}    0.26{col 46}{space 3}0.795{col 54}{space 4}-.2320505{col 67}{space 3} .3028953
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} -.873711{col 26}{space 2} .3692016{col 37}{space 1}   -2.37{col 46}{space 3}0.018{col 54}{space 4}-1.597333{col 67}{space 3}-.1500892
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 23 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-351.17226}  
Iteration 1:{space 3}log likelihood = {res:-347.79973}  
Iteration 2:{space 3}log likelihood = {res:-347.76286}  
Iteration 3:{space 3}log likelihood = {res:-347.76286}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       987
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}      6.82
{txt}{col 49}Prob > chi2{col 67}= {res}    0.2345
{txt}Log likelihood = {res}-347.76286{txt}{col 49}Pseudo R2{col 67}= {res}    0.0097

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .1093613{col 26}{space 2} .2055505{col 37}{space 1}    0.53{col 46}{space 3}0.595{col 54}{space 4}-.2935103{col 67}{space 3} .5122328
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0781257{col 26}{space 2} .0438099{col 37}{space 1}    1.78{col 46}{space 3}0.075{col 54}{space 4}-.0077402{col 67}{space 3} .1639915
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0116743{col 26}{space 2} .0064027{col 37}{space 1}    1.82{col 46}{space 3}0.068{col 54}{space 4}-.0008747{col 67}{space 3} .0242234
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0360955{col 26}{space 2} .0471977{col 37}{space 1}    0.76{col 46}{space 3}0.444{col 54}{space 4}-.0564102{col 67}{space 3} .1286013
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .1193443{col 26}{space 2} .2074311{col 37}{space 1}    0.58{col 46}{space 3}0.565{col 54}{space 4}-.2872131{col 67}{space 3} .5259017
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.453163{col 26}{space 2} .5768626{col 37}{space 1}   -5.99{col 46}{space 3}0.000{col 54}{space 4}-4.583793{col 67}{space 3}-2.322533
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 24 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-274.90864}  
Iteration 1:{space 3}log likelihood = {res: -268.6229}  
Iteration 2:{space 3}log likelihood = {res: -268.3663}  
Iteration 3:{space 3}log likelihood = {res:-268.36594}  
Iteration 4:{space 3}log likelihood = {res:-268.36594}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       983
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     13.09
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0226
{txt}Log likelihood = {res}-268.36594{txt}{col 49}Pseudo R2{col 67}= {res}    0.0238

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.3899221{col 26}{space 2} .3167834{col 37}{space 1}   -1.23{col 46}{space 3}0.218{col 54}{space 4}-1.010806{col 67}{space 3} .2309619
{txt}{space 3}education {c |}{col 14}{res}{space 2} .1196107{col 26}{space 2} .0494718{col 37}{space 1}    2.42{col 46}{space 3}0.016{col 54}{space 4} .0226478{col 67}{space 3} .2165737
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0156185{col 26}{space 2} .0065269{col 37}{space 1}    2.39{col 46}{space 3}0.017{col 54}{space 4} .0028261{col 67}{space 3}  .028411
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0632955{col 26}{space 2} .0542177{col 37}{space 1}    1.17{col 46}{space 3}0.243{col 54}{space 4}-.0429693{col 67}{space 3} .1695603
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.4049749{col 26}{space 2} .2397139{col 37}{space 1}   -1.69{col 46}{space 3}0.091{col 54}{space 4}-.8748056{col 67}{space 3} .0648557
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.611307{col 26}{space 2}  .688198{col 37}{space 1}   -5.25{col 46}{space 3}0.000{col 54}{space 4}-4.960151{col 67}{space 3}-2.262464
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 25 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-287.30779}  
Iteration 1:{space 3}log likelihood = {res:-278.05744}  
Iteration 2:{space 3}log likelihood = {res: -278.0356}  
Iteration 3:{space 3}log likelihood = {res: -278.0356}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       415
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     18.54
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0023
{txt}Log likelihood = {res} -278.0356{txt}{col 49}Pseudo R2{col 67}= {res}    0.0323

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}-.7238462{col 26}{space 2} .3324335{col 37}{space 1}   -2.18{col 46}{space 3}0.029{col 54}{space 4}-1.375404{col 67}{space 3}-.0722884
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0885468{col 26}{space 2} .0453313{col 37}{space 1}    1.95{col 46}{space 3}0.051{col 54}{space 4} -.000301{col 67}{space 3} .1773946
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0241856{col 26}{space 2} .0070675{col 37}{space 1}    3.42{col 46}{space 3}0.001{col 54}{space 4} .0103336{col 67}{space 3} .0380376
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0353006{col 26}{space 2} .0587025{col 37}{space 1}   -0.60{col 46}{space 3}0.548{col 54}{space 4}-.1503553{col 67}{space 3} .0797541
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .3191979{col 26}{space 2} .2101496{col 37}{space 1}    1.52{col 46}{space 3}0.129{col 54}{space 4}-.0926879{col 67}{space 3} .7310836
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.945549{col 26}{space 2} .6663785{col 37}{space 1}   -2.92{col 46}{space 3}0.004{col 54}{space 4}-3.251626{col 67}{space 3}-.6394707
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 26 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-534.02557}  
Iteration 1:{space 3}log likelihood = {res:-524.67868}  
Iteration 2:{space 3}log likelihood = {res:-524.63048}  
Iteration 3:{space 3}log likelihood = {res:-524.63048}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       907
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     18.79
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0021
{txt}Log likelihood = {res}-524.63048{txt}{col 49}Pseudo R2{col 67}= {res}    0.0176

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .2517451{col 26}{space 2} .1605143{col 37}{space 1}    1.57{col 46}{space 3}0.117{col 54}{space 4}-.0628572{col 67}{space 3} .5663474
{txt}{space 3}education {c |}{col 14}{res}{space 2}  .113788{col 26}{space 2} .0331819{col 37}{space 1}    3.43{col 46}{space 3}0.001{col 54}{space 4} .0487527{col 67}{space 3} .1788232
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0141013{col 26}{space 2} .0049051{col 37}{space 1}    2.87{col 46}{space 3}0.004{col 54}{space 4} .0044874{col 67}{space 3} .0237152
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0529021{col 26}{space 2} .0364785{col 37}{space 1}   -1.45{col 46}{space 3}0.147{col 54}{space 4}-.1243988{col 67}{space 3} .0185945
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.1088328{col 26}{space 2} .1530575{col 37}{space 1}   -0.71{col 46}{space 3}0.477{col 54}{space 4}-.4088199{col 67}{space 3} .1911544
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.062548{col 26}{space 2} .4626263{col 37}{space 1}   -4.46{col 46}{space 3}0.000{col 54}{space 4}-2.969279{col 67}{space 3}-1.155817
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 27 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-642.00256}  
Iteration 1:{space 3}log likelihood = {res:-637.78607}  
Iteration 2:{space 3}log likelihood = {res:-637.78276}  
Iteration 3:{space 3}log likelihood = {res:-637.78276}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       976
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}      8.44
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1336
{txt}Log likelihood = {res}-637.78276{txt}{col 49}Pseudo R2{col 67}= {res}    0.0066

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .2424498{col 26}{space 2} .1517899{col 37}{space 1}    1.60{col 46}{space 3}0.110{col 54}{space 4}-.0550529{col 67}{space 3} .5399524
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0748055{col 26}{space 2} .0347935{col 37}{space 1}    2.15{col 46}{space 3}0.032{col 54}{space 4} .0066115{col 67}{space 3} .1429995
{txt}{space 9}age {c |}{col 14}{res}{space 2}  .001318{col 26}{space 2} .0046684{col 37}{space 1}    0.28{col 46}{space 3}0.778{col 54}{space 4}-.0078318{col 67}{space 3} .0104678
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0218477{col 26}{space 2} .0330471{col 37}{space 1}   -0.66{col 46}{space 3}0.509{col 54}{space 4}-.0866188{col 67}{space 3} .0429233
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .1099072{col 26}{space 2} .1367721{col 37}{space 1}    0.80{col 46}{space 3}0.422{col 54}{space 4}-.1581612{col 67}{space 3} .3779757
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.291482{col 26}{space 2} .4295036{col 37}{space 1}   -3.01{col 46}{space 3}0.003{col 54}{space 4}-2.133293{col 67}{space 3}-.4496701
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 28 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-352.47417}  
Iteration 1:{space 3}log likelihood = {res:-346.47031}  
Iteration 2:{space 3}log likelihood = {res:-346.35644}  
Iteration 3:{space 3}log likelihood = {res:-346.35641}  
Iteration 4:{space 3}log likelihood = {res:-346.35641}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       981
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     12.24
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0317
{txt}Log likelihood = {res}-346.35641{txt}{col 49}Pseudo R2{col 67}= {res}    0.0174

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .4374411{col 26}{space 2} .2051712{col 37}{space 1}    2.13{col 46}{space 3}0.033{col 54}{space 4} .0353129{col 67}{space 3} .8395692
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0444458{col 26}{space 2} .0435962{col 37}{space 1}    1.02{col 46}{space 3}0.308{col 54}{space 4}-.0410013{col 67}{space 3} .1298928
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0067651{col 26}{space 2}  .006282{col 37}{space 1}    1.08{col 46}{space 3}0.282{col 54}{space 4}-.0055475{col 67}{space 3} .0190776
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0349629{col 26}{space 2} .0462079{col 37}{space 1}    0.76{col 46}{space 3}0.449{col 54}{space 4} -.055603{col 67}{space 3} .1255287
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.4694782{col 26}{space 2}  .202387{col 37}{space 1}   -2.32{col 46}{space 3}0.020{col 54}{space 4}-.8661494{col 67}{space 3} -.072807
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.280887{col 26}{space 2} .6182895{col 37}{space 1}   -3.69{col 46}{space 3}0.000{col 54}{space 4}-3.492712{col 67}{space 3}-1.069062
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 29 =========

note: 0.treated omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-471.71675}  
Iteration 1:{space 3}log likelihood = {res:-461.54189}  
Iteration 2:{space 3}log likelihood = {res:-461.41686}  
Iteration 3:{space 3}log likelihood = {res:-461.41683}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       890
{txt}{col 49}LR chi2({res}4{txt}){col 67}= {res}     20.60
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0004
{txt}Log likelihood = {res}-461.41683{txt}{col 49}Pseudo R2{col 67}= {res}    0.0218

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Control  {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 3}education {c |}{col 14}{res}{space 2} .0945872{col 26}{space 2} .0350517{col 37}{space 1}    2.70{col 46}{space 3}0.007{col 54}{space 4} .0258872{col 67}{space 3} .1632872
{txt}{space 9}age {c |}{col 14}{res}{space 2}-.0047598{col 26}{space 2} .0051699{col 37}{space 1}   -0.92{col 46}{space 3}0.357{col 54}{space 4}-.0148925{col 67}{space 3}  .005373
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0947908{col 26}{space 2} .0397003{col 37}{space 1}   -2.39{col 46}{space 3}0.017{col 54}{space 4}-.1726021{col 67}{space 3}-.0169796
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .1050397{col 26}{space 2} .1639778{col 37}{space 1}    0.64{col 46}{space 3}0.522{col 54}{space 4}-.2163508{col 67}{space 3} .4264302
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} -1.31998{col 26}{space 2} .4732365{col 37}{space 1}   -2.79{col 46}{space 3}0.005{col 54}{space 4}-2.247507{col 67}{space 3}-.3924537
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 30 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-377.53861}  
Iteration 1:{space 3}log likelihood = {res:-373.23694}  
Iteration 2:{space 3}log likelihood = {res:  -373.183}  
Iteration 3:{space 3}log likelihood = {res:-373.18298}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       964
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}      8.71
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1212
{txt}Log likelihood = {res}-373.18298{txt}{col 49}Pseudo R2{col 67}= {res}    0.0115

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2}   .51523{col 26}{space 2} .6579898{col 37}{space 1}    0.78{col 46}{space 3}0.434{col 54}{space 4}-.7744062{col 67}{space 3} 1.804866
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0899438{col 26}{space 2} .0379622{col 37}{space 1}    2.37{col 46}{space 3}0.018{col 54}{space 4} .0155393{col 67}{space 3} .1643482
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0153223{col 26}{space 2} .0066672{col 37}{space 1}    2.30{col 46}{space 3}0.022{col 54}{space 4} .0022548{col 67}{space 3} .0283898
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0198317{col 26}{space 2} .0491229{col 37}{space 1}   -0.40{col 46}{space 3}0.686{col 54}{space 4}-.1161109{col 67}{space 3} .0764475
{txt}{space 6}gender {c |}{col 14}{res}{space 2} .1207703{col 26}{space 2} .1912233{col 37}{space 1}    0.63{col 46}{space 3}0.528{col 54}{space 4}-.2540205{col 67}{space 3}  .495561
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.200246{col 26}{space 2} .5476416{col 37}{space 1}   -5.84{col 46}{space 3}0.000{col 54}{space 4}-4.273604{col 67}{space 3}-2.126888
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

======== Regression for level: 32 =========

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-399.73056}  
Iteration 1:{space 3}log likelihood = {res:-379.74458}  
Iteration 2:{space 3}log likelihood = {res:-378.90421}  
Iteration 3:{space 3}log likelihood = {res:-378.90288}  
Iteration 4:{space 3}log likelihood = {res:-378.90288}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       944
{txt}{col 49}LR chi2({res}5{txt}){col 67}= {res}     41.66
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-378.90288{txt}{col 49}Pseudo R2{col 67}= {res}    0.0521

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treated {c |}
{space 4}Treated  {c |}{col 14}{res}{space 2} .4272561{col 26}{space 2} .2891984{col 37}{space 1}    1.48{col 46}{space 3}0.140{col 54}{space 4}-.1395623{col 67}{space 3} .9940746
{txt}{space 3}education {c |}{col 14}{res}{space 2} .0353131{col 26}{space 2}  .033461{col 37}{space 1}    1.06{col 46}{space 3}0.291{col 54}{space 4}-.0302693{col 67}{space 3} .1008954
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0240882{col 26}{space 2} .0055952{col 37}{space 1}    4.31{col 46}{space 3}0.000{col 54}{space 4} .0131219{col 67}{space 3} .0350545
{txt}{space 2}occupation {c |}{col 14}{res}{space 2} .0864676{col 26}{space 2} .0536251{col 37}{space 1}    1.61{col 46}{space 3}0.107{col 54}{space 4}-.0186357{col 67}{space 3} .1915708
{txt}{space 6}gender {c |}{col 14}{res}{space 2}-.6613701{col 26}{space 2} .1884805{col 37}{space 1}   -3.51{col 46}{space 3}0.000{col 54}{space 4}-1.030785{col 67}{space 3}-.2919552
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.725583{col 26}{space 2} .5045712{col 37}{space 1}   -5.40{col 46}{space 3}0.000{col 54}{space 4}-3.714525{col 67}{space 3}-1.736642
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.  coefplot cntry_plac*, xline(0) xline(-0.368, lcolor(blue)) keep(1.treated) ylabel("") xtitle(" " "Coefficient") ///
>  plotlabels("France" "Belgium" "The Netherlands" "Germany" "Italy" "Luxembourg" "Denmark" "Ireland" "Great Britain" ///
>  "Greece" "Spain" "Portugal" "Finland" "Sweden" "Austria" "Cyprus" "Czech Republic" "Estonia" "Hungary" "Latvia" ///
>  "Lithuania" "Malta" "Poland" "Slovakia" "Slovenia" "Bulgaria" "Romania" "Croatia") ///
>  note("Portugese coefficient in blue dashed line. Zero in grey dashed line.", size(small) position(5)) legend(pos(9) col(1))
{res}{txt}(cntry_plac_29: no coefficients found, all dropped, or none kept)
{res}{txt}
{com}. graph save FigureA8.gph, replace
{txt}(note: file FigureA8.gph not found)
{res}{txt}(file FigureA8.gph saved)

{com}. graph export FigureA8.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA8.pdf written in PDF format)

{com}. 
.  
. 
.                                                                                                         ******************
.                                                                                                         ***  FIGURE A9 ***
.                                                                                                         ******************
. keep if v6 == 13 // keep if Portugal
{txt}(26,665 observations deleted)

{com}. teffects nnmatch (trust_plt age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(1)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       980
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}          9
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0627416{col 26}{space 2}  .055924{col 37}{space 1}   -1.12{col 46}{space 3}0.262{col 54}{space 4}-.1723507{col 67}{space 3} .0468674
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh1
{txt}
{com}. teffects nnmatch (trust_plt age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(2)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       980
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          2
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         2
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         10
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0582248{col 26}{space 2}  .049065{col 37}{space 1}   -1.19{col 46}{space 3}0.235{col 54}{space 4}-.1543905{col 67}{space 3} .0379408
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh2
{txt}
{com}. teffects nnmatch (trust_plt age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(3)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       980
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          3
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         3
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         10
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0594168{col 26}{space 2} .0460852{col 37}{space 1}   -1.29{col 46}{space 3}0.197{col 54}{space 4} -.149742{col 67}{space 3} .0309084
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh3
{txt}
{com}. teffects nnmatch (trust_plt age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(4)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       980
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          4
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         4
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         14
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0660941{col 26}{space 2} .0417034{col 37}{space 1}   -1.58{col 46}{space 3}0.113{col 54}{space 4}-.1478312{col 67}{space 3}  .015643
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh4
{txt}
{com}. teffects nnmatch (trust_plt age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(5)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       980
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          5
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         5
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         14
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0720199{col 26}{space 2} .0396368{col 37}{space 1}   -1.82{col 46}{space 3}0.069{col 54}{space 4}-.1497067{col 67}{space 3} .0056668
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh5
{txt}
{com}. teffects nnmatch (trust_plt age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(6)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       980
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          6
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         6
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         17
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0764276{col 26}{space 2} .0394784{col 37}{space 1}   -1.94{col 46}{space 3}0.053{col 54}{space 4}-.1538039{col 67}{space 3} .0009486
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh6
{txt}
{com}. teffects nnmatch (trust_plt age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(7)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       980
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          7
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         7
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         17
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}   trust_plt{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0709836{col 26}{space 2} .0384809{col 37}{space 1}   -1.84{col 46}{space 3}0.065{col 54}{space 4}-.1464048{col 67}{space 3} .0044376
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh7
{txt}
{com}. 
. coefplot nneigh*, xline(0) legend(position(6) rows(1) subtitle("N of Neighbours")) ylabel("") levels(95 90) ///
> plotlabels("1" "2" "3" "4" "5" "6" "7") xtitle(" " "Coefficient") note("Confidence intervals at 99% and 95%", size(small) position(5)) 
{res}{txt}
{com}. graph save FigureA9.gph, replace
{txt}(note: file FigureA9.gph not found)
{res}{txt}(file FigureA9.gph saved)

{com}. graph export FigureA9.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA9.pdf written in PDF format)

{com}. 
. 
.  
.                                                                                                         *******************
.                                                                                                         ***  FIGURE A10 ***
.                                                                                                         *******************
.                                                                                                         
. 
. teffects nnmatch (econ_expec age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(1)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       967
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         10
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0581831{col 26}{space 2} .0799556{col 37}{space 1}   -0.73{col 46}{space 3}0.467{col 54}{space 4}-.2148931{col 67}{space 3} .0985269
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh1_econ
{txt}
{com}. teffects nnmatch (econ_expec age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(2)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       967
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          2
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         2
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         10
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0923354{col 26}{space 2}  .071629{col 37}{space 1}   -1.29{col 46}{space 3}0.197{col 54}{space 4}-.2327257{col 67}{space 3} .0480549
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh2_econ
{txt}
{com}. teffects nnmatch (econ_expec age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(3)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       967
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          3
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         3
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         14
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.1071288{col 26}{space 2} .0657136{col 37}{space 1}   -1.63{col 46}{space 3}0.103{col 54}{space 4} -.235925{col 67}{space 3} .0216674
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh3_econ
{txt}
{com}. teffects nnmatch (econ_expec age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(4)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       967
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          4
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         4
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         14
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.1104269{col 26}{space 2} .0608221{col 37}{space 1}   -1.82{col 46}{space 3}0.069{col 54}{space 4} -.229636{col 67}{space 3} .0087822
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh4_econ
{txt}
{com}. teffects nnmatch (econ_expec age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(5)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       967
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          5
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         5
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         15
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.1130232{col 26}{space 2} .0566944{col 37}{space 1}   -1.99{col 46}{space 3}0.046{col 54}{space 4}-.2241421{col 67}{space 3}-.0019043
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh5_econ
{txt}
{com}. teffects nnmatch (econ_expec age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(6)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       967
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          6
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         6
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         17
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.1250404{col 26}{space 2} .0555363{col 37}{space 1}   -2.25{col 46}{space 3}0.024{col 54}{space 4}-.2338895{col 67}{space 3}-.0161913
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh6_econ
{txt}
{com}. teffects nnmatch (econ_expec age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(7)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}       967
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          7
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         7
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         17
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_expec{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.1241652{col 26}{space 2} .0553766{col 37}{space 1}   -2.24{col 46}{space 3}0.025{col 54}{space 4}-.2327013{col 67}{space 3}-.0156291
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh7_econ
{txt}
{com}. 
. coefplot nneigh*_econ, xline(0) legend(position(6) rows(1) subtitle("N of Neighbours")) ylabel("") levels(95 90) ///
> plotlabels("1" "2" "3" "4" "5" "6" "7") xtitle(" " "Coefficient") note("Confidence intervals at 99% and 95%", size(small) position(5)) 
{res}{txt}
{com}. graph save FigureA10.gph, replace
{txt}(note: file FigureA10.gph not found)
{res}{txt}(file FigureA10.gph saved)

{com}. graph export FigureA10.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA10.pdf written in PDF format)

{com}. 
.                                                                                                         
.                                                                                                          
.                                                                                                         *******************
.                                                                                                         ***  FIGURE A11 ***
.                                                                                                         *******************
. teffects nnmatch (econ_evals age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(1)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}     1,022
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         10
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0381273{col 26}{space 2}  .051169{col 37}{space 1}   -0.75{col 46}{space 3}0.456{col 54}{space 4}-.1384166{col 67}{space 3}  .062162
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh1_econev
{txt}
{com}. teffects nnmatch (econ_evals age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(2)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}     1,022
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          2
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         2
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         10
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0482281{col 26}{space 2} .0528126{col 37}{space 1}   -0.91{col 46}{space 3}0.361{col 54}{space 4}-.1517389{col 67}{space 3} .0552826
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh2_econev
{txt}
{com}. teffects nnmatch (econ_evals age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(3)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}     1,022
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          3
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         3
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         11
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2} -.061841{col 26}{space 2} .0510117{col 37}{space 1}   -1.21{col 46}{space 3}0.225{col 54}{space 4} -.161822{col 67}{space 3}   .03814
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh3_econev
{txt}
{com}. teffects nnmatch (econ_evals age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(4)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}     1,022
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          4
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         4
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         15
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0777227{col 26}{space 2} .0484227{col 37}{space 1}   -1.61{col 46}{space 3}0.108{col 54}{space 4}-.1726294{col 67}{space 3}  .017184
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh4_econev
{txt}
{com}. teffects nnmatch (econ_evals age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(5)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}     1,022
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          5
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         5
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         15
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0913647{col 26}{space 2} .0467496{col 37}{space 1}   -1.95{col 46}{space 3}0.051{col 54}{space 4}-.1829922{col 67}{space 3} .0002628
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh5_econev
{txt}
{com}. teffects nnmatch (econ_evals age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(6)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}     1,022
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          6
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         6
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         18
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0901645{col 26}{space 2} .0463213{col 37}{space 1}   -1.95{col 46}{space 3}0.052{col 54}{space 4}-.1809525{col 67}{space 3} .0006235
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh6_econev
{txt}
{com}. teffects nnmatch (econ_evals age education occupation gender) (treated), ematch(gender) biasadj(age education occupation) nneighbor(7)
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}     1,022
{txt:Estimator}{col 16}:{res: nearest-neighbor matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          7
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         7
{txt:Distance metric: }{res:Mahalanobis}{col 63}{txt:max }{col 67}{txt:=}         18
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}   AI Robust
{col 1}  econ_evals{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE          {txt}{c |}
{space 5}treated {c |}
{space 3}(Treated  {c |}
{space 9}vs  {c |}
{space 3}Control)  {c |}{col 14}{res}{space 2}-.0822179{col 26}{space 2} .0459631{col 37}{space 1}   -1.79{col 46}{space 3}0.074{col 54}{space 4} -.172304{col 67}{space 3} .0078681
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store nneigh7_econev
{txt}
{com}. 
. coefplot nneigh*_econev, xline(0) legend(position(6) rows(1) subtitle("N of Neighbours")) ylabel("") levels(95 90) ///
> plotlabels("1" "2" "3" "4" "5" "6" "7") xtitle(" " "Coefficient") note("Confidence intervals at 99% and 95%", size(small) position(5)) 
{res}{txt}
{com}. graph save FigureA11.gph, replace
{txt}(note: file FigureA11.gph not found)
{res}{txt}(file FigureA11.gph saved)

{com}. graph export FigureA11.pdf, replace
{txt}(file /Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/FigureA11.pdf written in PDF format)

{com}. 
. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/stuartturnbulldugarte/Dropbox/Interventions & Trust/PSRM_replication/logreplication_study1.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}22 Oct 2021, 17:03:15
{txt}{.-}
{smcl}
{txt}{sf}{ul off}